Methods and apparatus for mobile additive manufacturing

ABSTRACT

The present disclosure provides various advancements for mobile and automated processing utilizing additive manufacturing. The present disclosure includes methods for the utilization of mobile and automated processing apparatus and may include examples of sealcoating operations. In some examples, omnidirectional drive systems such as Mecanum wheels may create novel operational aspects. Artificial intelligence techniques may enhance operations and may be used to create model for the processing apparatus.

CROSS REFERENCE TO RELATED APPLICATION

This application claims priority to the U.S. Non-Provisional patentapplication Ser. No. 16/324,058, filed on Feb. 7, 2019 as a ContinuationApplication, which in turn claims priority as a U.S. National Stage(371) entry of the U.S. PCT Application S/N PCT/US18/46749 filed on Aug.14, 2018. The contents of each are hereby incorporated by reference.

This application also references the U.S. Non-Provisional patentapplication Ser. No. 15/641,509 filed on Jul. 7, 2017 the contents ofwhich is hereby incorporated by reference.

FIELD OF THE INVENTION

The present disclosure relates to methods and apparatus that supportmobile additive material processing. Robotic and human controlledmobility may be combined with additive manufacturing techniques that“print” or additively deliver materials to specific locations oversignificant distances. The methods and apparatus may be applied to theproductions of advanced building structures and roadways.

BACKGROUND OF THE INVENTION

A known class of approaches to material fabrication can be classified asadditive manufacturing. Material in various forms, including solid,powder, gel, gas, or liquid forms may be processed in such a manner todeposit or lock in material in a target location in space.

Numerous techniques may be utilized to perform additive manufacturing.In extrusion processes, materials in wire or filament form arecontrolled by an extrusion head which may be moved above a work area.The use of multiple extrusion heads and extrusion material may allow forboth permanent and temporary structures to be formed. By building theextruded material in layers or in regions, complex shapes may be formedin three dimensions. However, the technology is limited by thedimensions of the work space—the ability of the head or heads to move inthe two dimensions of a plane and by the dimension of the ability of thehead to move vertically relative to a planar support structure. Theremay be numerous variations on this form of additive manufacturing.

A different class of additive manufacturing may be classified asStereolithography. In this class, a light or heat source is used totransform the material in space. In some Stereolithographyimplementations, the work support plane is submerged in a photoactive orthermo-active liquid and a laser or other light or heat source israstered across a thin surface layer of the liquid between the supportstructure and the top level of the liquid. By translating the supportstructure down a layer into the liquid, the fluent nature of the liquidreforms a thin layer of new unreacted material over the work surface orthe previously processed layer.

Versions of Stereolithography may also work with powder formed startingmaterial. The powder may be shaped into a thin layer and then spatiallydefined. Lasers may be used to transform portions of the layer into asolidified material. In other examples, other energy sources such as,for example, electron beams, may be used to transform the powder.Various materials including metals, insulators and plastics may beformed into three dimensional shapes by these processing techniques.

A different type of processing occurs when a print head is used todeposit material onto the powder. The deposit may chemically react withthe powder or may be an adhesive that consolidates the powder into anadhered location. The prevalence of high resolution printing technologymay make this type of additive manufacturing process cost effective.

The field is both established, with versions of additive manufacturingbeing practiced for decades, and emerging, with new techniques andmaterials being defined with rapidity. The technology may be currentlylimited by the dimensions of objects that may be produced. Accordingly,it may be desirable to develop methods and apparatus that allow additivemanufacturing techniques and apparatus to be independently mobile and tocontinuously improve these new methods and apparatus.

SUMMARY OF THE INVENTION

Accordingly, the present disclosure provides description for methods andapparatus that allow for mobile additive manufacturing. In someexamples, the mobile additive manufacturing apparatus may act in anindependent or automated manner. The apparatus that performs the mobileadditive manufacturing may be called an Addibot (ADDItive roBOT).

An important characteristic of additive manufacturing apparatus may bethat material is added to a product in a controlled manner that isdriven by a digital model that resides in a controller. Through theprocessing of the additive manufacturing apparatus the digitalrepresentation may be translated to a physical approximation of materialplaced in three-dimensional space.

In some examples, a team of mobile additive manufacturing apparatus maybe applied as a system. Implementations may include one or more of thefollowing features. The method may provide a system for applying a firstmaterial to a surface and may also provide for multiple materials beingapplied to the surface. A process of using the system may include stepsas follows: a first material may be loaded into each of a first mobileadditive manufacturing apparatus and a second mobile additivemanufacturing apparatus. In some examples, each of the first mobilemanufacturing apparatus and the second mobile manufacturing apparatusmay comprise: a navigation system to determine location, a mobileadditive manufacturing apparatus controller capable of executingalgorithms and providing control signals, a vision system capable ofscanning the surface and measuring a topography of the surface, anadditive manufacturing system to deposit at least the first material ina prescribed location on the surface according to a digital modelprocessed by the mobile additive manufacturing apparatus controller, apower system capable of providing power to operate at least the drivesystem, navigation system, mobile additive manufacturing apparatuscontroller and additive manufacturing system, and a communicationsystem, wherein the communication system provides communication betweenat least the first mobile additive manufacturing apparatus, the secondmobile additive manufacturing apparatus and the artificial intelligenceprocessing system. The process may include communicating an objectivefor applying the material to the surface to an artificial intelligenceprocessing system, wherein the artificial intelligence processing systemcomprises a program which executes at least a first algorithm. Theprocess may include receiving information at the artificial intelligenceprocessing system from the first mobile additive manufacturing apparatuscomprising at least a location determined by the navigation system ofthe first mobile additive manufacturing apparatus. The method mayinclude processing the received information with the artificialintelligence processing system with at least a first artificialintelligence algorithm. And, the method may include communicating atleast movement plans to at least each of the first mobile additivemanufacturing apparatus and the second mobile additive manufacturingapparatus of the team. Implementations of the described techniques mayinclude hardware, a method or process, or computer software on acomputer-accessible medium.

In some implementations, the method may also include implementationswhere the artificial intelligence processing system comprises anartificial intelligence processing chip.

In some implementations, the method may further include receivinginformation at the artificial intelligence processing system from thefirst mobile additive manufacturing apparatus comprising at least aimage determined by the vision system of the first mobile additivemanufacturing apparatus. Such methods may also include processing thereceived information with the artificial intelligence processing systemwith at least a second artificial intelligence algorithm. And suchmethods may also include communicating at least deposition plans of atleast the first material to at least each of the first mobile additivemanufacturing apparatus and the second mobile additive manufacturingapparatus of the team.

In some implementations, the method may further include examples whereinat least the first mobile additive manufacturing apparatus comprises anartificial intelligence processing chip.

In some implementations, the method may further include communicating atleast a second deposition plan of at least a second material comprisinga paint material.

In some implementations, the method may also include communicating atleast movement plans of the first mobile additive manufacturing systemand the second mobile additive manufacturing system to a roadwayinformation processing system, wherein the roadway informationprocessing system communicates information to vehicles using theroadway, and wherein the communication of information related to themovement plan to the vehicles can facilitate their safe movement throughthe portion of the roadway occupied by at least the first mobileadditive manufacturing system.

In some examples, a mobile additive manufacturing apparatus fordepositing a first seal coating material may have a number of elementsincluding: a navigation system to determine location, a controllercapable of executing algorithms and providing control signals, a visionsystem capable of scanning a first surface and measuring a topography ofthe surface as the mobile additive manufacturing apparatus moves overthe first surface, a drive system to move the additive manufacturingapparatus, an additive manufacturing system to deposit at least thefirst material for seal coating in a prescribed location on the surfaceaccording to a digital model processed by the controller, and a powersystem capable of providing power to operate at least the drive system,navigation system, controller and additive manufacturing system. Themobile additive manufacturing system may also include a chassis, whereinthe chassis supports all of the navigation system, the controller, thevision system, the drive system, the additive manufacturing system andthe power system; and a rotary dispensing system, wherein the rotarydispensing system comprises a rotary gantry, wherein the rotary gantryis moved by a motor driving an element around a central axis supportedby the chassis.

In some of such examples, the apparatus may also include rotary gantrywhere these rotary gantries support at least a first spray dispensingnozzle, and wherein the first seal coating material is passed throughthe rotary dispensing system to the nozzle.

In some further examples, the apparatus may include examples wherein thedrive system comprises at least a first omnidirectional wheel directlyattached to a first motor, wherein the drive system can move the mobileadditive manufacturing apparatus in more directions than forward andbackward by adjusting the operating conditions of the first motor.

In some further examples, the apparatus may include examples wherein therotary gantry moves the rotation angle of the rotary gantry relative tothe chassis in response to the adjusted conditions of the first motor.

Still further examples may derive when the apparatus includes exampleswherein the rotary gantry supports at least a first sensor, wherein thesensor senses the rate of dispensing of the first seal coating material.

In some examples, the apparatus may include examples where the rotarygantry comprises at least a first squeegee and at least a first nozzle,wherein the rotary gantry continuously rotates around the central axiswhile the nozzle dispenses the first seal coating material, and whereinthe rotating squeegee spreads out the first seal coating material on thefirst surface as the mobile additive manufacturing apparatus movesacross the first surface. In further examples, the apparatus may furtherinclude a second squeegee, wherein the first squeegee and the secondsqueegee are deployed on distal ends of the rotary gantry, and whereinat least the first nozzle dispenses the first seal coating material intoa space between the first squeegee and the second squeegee. In some ofthese examples, this apparatus may also include examples wherein therotary gantry further comprises at least a first sensor, wherein thefirst sensor measures an amount of material dispensed by the nozzle.

Still further examples may be configured where the apparatus alsoincludes at least a second sensor, wherein the second sensor measures anamount of material dispensed by the nozzle.

Implementations may include one or more of the following features. Insome examples, a method of seal coating a first surface, may includeexamples with a step for loading at least a first seal coating materialinto at least a first mobile additive manufacturing apparatus. The firstmobile manufacturing apparatus may include: a navigation system todetermine location, a controller capable of executing algorithms andproviding control signals, a vision system capable of scanning a firstsurface and measuring a topography of the surface as the mobile additivemanufacturing apparatus moves over the first surface, a drive system tomove the additive manufacturing apparatus, an additive manufacturingsystem to deposit at least the first material for seal coating in aprescribed location on the surface according to a digital modelprocessed by the controller, a power system capable of providing powerto operate at least the drive system, navigation system, controller andadditive manufacturing system, a chassis, wherein the chassis supportsall of the navigation system, the controller, the vision system, thedrive system, the additive manufacturing system and the power system,and a rotary dispensing system, wherein the rotary dispensing systemcomprises a rotary gantry, wherein the rotary gantry is moved by a motordriving an element around a central axis supported by the chassis. Themethod may include the step of moving the first mobile additivemanufacturing apparatus with the drive system, wherein the amount ofmovement is controlled by the digital model. And, the method may includethe step of dispensing the seal coating material on the first surfacewhile the first mobile additive manufacturing apparatus is moving,wherein the amount of the seal coating material dispensed is controlledby the digital model.

In some implementations, the method may further include examples wherethe controller comprises an artificial intelligence processing chip, andan artificial intelligence algorithm is used to create the digitalmodel.

In some implementations, the method may further include examples wherethe rotary gantry supports at least a first spray dispensing nozzle, andwherein the first seal coating material is passed through the rotarydispensing system to the nozzle. In some of these examples, the methodmay dispense material upon one or more of a driveway, a roadway, aparking lot or a roof.

In some implements the method may include examples where the rotarygantry comprises at least a first squeegee and at least a first nozzle,wherein the rotary gantry continuously rotates around the central axiswhile the nozzle dispenses the first seal coating material, and whereinthe rotating squeegee spreads out the first seal coating material on thefirst surface as the mobile additive manufacturing apparatus movesacross the first surface.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, that are incorporated in and constitute apart of this specification, illustrate several examples of the inventionand, together with the description, serve to explain the principles ofthe invention:

FIG. 1A illustrates a block diagram of the exemplary general componentsof a mobile automated additive manufacturing apparatus.

FIG. 1B illustrates examples of omnidirectional drive system types.

FIG. 1C illustrates examples of the interaction of artificialintelligence software and hardware with general components of a mobileautomated additive manufacturing apparatus.

FIG. 1D illustrates an exemplary rotating spray dispensing system.

FIG. 1E illustrates an exemplary squeegee dispensing and applicationsystem.

FIGS. 2 and 2B illustrate perspective views of an exemplary mobileautomated additive manufacturing apparatus that may be useful for RoadSurface Treatment.

FIG. 3 illustrates a processor and controller that may be useful invarious examples of mobile automated additive manufacturing apparatus.

FIGS. 4 and 4B illustrate exemplary methods related to various examplesof mobile automated additive manufacturing apparatus.

FIG. 5 illustrates aspects of team action of mobile automated additivemanufacturing apparatus.

FIG. 6 illustrates an exemplary Addibot in concert with features of anadvanced roadway.

FIG. 7 illustrates an exemplary roadway with features requiring repairprocessing.

FIG. 8A illustrates exemplary methods related to repair of exemplary pothole type road defects.

FIG. 8B illustrates exemplary methods related to repair of exemplarycrack type road defects.

FIGS. 9A-9F illustrate exemplary aspects of omnidirectional drivesystems.

FIGS. 10A-D illustrate exemplary aspects of paths that can be taken withomnidirectional drive systems.

DETAILED DESCRIPTION OF PREFERRED EXAMPLES

The present disclosure relates to methods and apparatus for mobileautomated additive manufacturing. As used herein, “mobile automatedadditive manufacturing” may include control of locomotion of an additivemanufacturing apparatus over a surface free of tracks or rails. A numberof descriptions of mobile additive manufacturing have been described bythe inventors in other specification including the U.S. Non-Provisionalpatent application Ser. No. 14/310,443, filed on Jun. 20, 2014 andentitled METHODS AND APPARATUS FOR MOBILE ADDITIVE MANUFACTURING, theU.S. Provisional Application Ser. 61/434,302 filed on Jun. 23, 2013, andthe U.S. Non-Provisional patent application Ser. No. 14/310,556, filedon Jun. 20, 2014 and entitled METHODS AND APPARATUS FOR MOBILE ADDITIVEMANUFACTURING OF ADVANCED STRUCTURES AND ROADWAYS. The content of thesethree applications is included herein by reference. Furthermore,concepts involving machine learning and more broadly artificialintelligence have been described and will be discussed in thisspecification. An example of exemplary machine learning protocols andassociated algorithms may be found within the U.S. Pat. No. 9,904,889entitled METHODS AND SYSTEMS FOR ARTIFICIAL COGNITION the contents ofwhich are included herein by reference.

The fields of building and roadway construction are also establishedwith regards to equipment used for tasks involving maintenance orconstruction of surfaces. Various pieces of equipment have beendeveloped to apply materials to a work site in these tasks, such assealcoating, defect repair, and construction of new objects. Many ofthese tools must be guided manually by human eyes and hands, or sufferfrom other problems regarding precision, bandwidth, and safety forworkers, that it may be desirable to introduce the above-stated meritsof additive manufacturing methods. Some emerging technologies in theseconstruction fields exhibit some additive manufacturing principles, suchas a huge cement extrusion device that prints castle walls inside itsworkspace, but still come with a host of issues that limit theireffectiveness in the field. Many of the merits of novel mobile additivemanufacturing may be directed towards solving or mitigating theseissues.

Referring to FIG. 1A, 100, some elements of an exemplary mobile additivemanufacturing system (110) may be found. The system may have a drivesystem 120 enabling transportation of the manufacturing system over asurface. The drive system 120 may function to move the apparatus on bothflat and shaped or curved topography. The drive system 120 may functionon wheels, balls, tracks, or other means of conveyance known in the art.In some examples, the use of automotive or truck frames either withtrailers or with modification directly to the frame itself may be used.The drive system 120 may incorporate a drive mechanism comprising anengine or motor that may act upon the conveyance elements such as wheelsor may utilize transmissions and axles to drive the conveyance elements.Various forms of directional or steering control may be possible. Insome examples, the differential control of multiple motors acting uponconveyance elements may allow for directional control. In otherexamples, the directional control may function by a steering system thatmoves the conveyance elements in ways other than in its drive sense. Insome examples the design of the wheels and the drive systems for thewheels can define omnidirectional drive systems. In some examples threeor four engineered wheels can be used to move the system in all lineardirections and rotary directions without an independent steering system.Such systems can create unique operational schemes for Addibotoperations where the portion that performs additive manufacturing can bemoved over surfaces without the drive system passing over the treatedsurface even when the system turns a corner or passes back along a path.

Referring to FIG. 1B, exemplary omnidirectional drive systems withexemplary wheel or wheel equivalent drive element configuration areillustrated. For example, at 101B an exemplary omni wheel is shown alongwith some 3, 4 and 5-wheel configurations. At 102B and exemplary Mecanumwheel is shown along with a 4-wheel configuration. Further, at 103B aspherical wheel-based system is illustrated. At 104B a rotatablecylindrical wheel example is illustrated. To varying degrees ofeffectiveness, these examples illustrate potential systems which couldgive a robotic base directional control without a standard steeringsystem. Uniquely, in a mobile additive manufacturing systemomnidirectional drive system when synergistically coupled with theoperations of additive manufacturing systems creates different modes ofoperation that are not possible in conventionally driven systems.

Referring again to FIG. 1A, the mobile additive manufacturing system 110may include a Navigation, Control and Sensing system 130 that mayfunction to determine a current location to a desired degree of accuracyas well as an orientation of the device at that location. Suchinformation may be useful in regulating direction control through thenavigation system and in determining other control variables such asspeed. The sensing system may provide other environmental information tothe control system such as temperature and humidity at the location andin some examples at a surface beneath the location of the system. Inaddition, the sensor and navigation elements may also function toprovide awareness of obstacles in the environment of the mobile additivemanufacturing apparatus. A separate vision, measurement and inspectionsystem may be present in some examples (a following discussion discussesthis in detail) and may interface with the control elements or sensingelements. The control elements may receive data in various forms and mayprocess the data utilizing computational hardware and programingalgorithms. The processing may produce control signals to engage themobile additive manufacturing apparatus to produce an environmentalchange such as adding material of various forms to createthree-dimensional surface characteristics such as a flat surface, asurface of defined topography or a surface where defects of varioustypes are affected with the addition of material. In other examples, theaddition of material may be used to create an image or anotherfunctional aspect such as a slip resistive coating or a tread cleaningfunction as examples.

The navigation element may utilize various protocols to generatelocation awareness. For example, the element may utilize GPS technology.In other examples, a local transceiver network may provide telemetrylocal relative location awareness through the use of RF systems, orlight-based systems such as a laser-based system. This local system mayfunction within an outdoor region or alternatively be set up to functionwithin a building. Cell phone-based telemetry, and other schemes such asseismic location detection may provide information for telemetry. Insome examples, the navigation element may provide a first ordertelemetry to an accuracy required to control movement of the apparatus,for example. The vision system (to be discussed) or other sensingelements may provide a next higher accuracy for calibration of location.Location marks may be present upon or within the surface and a sensorsuch as a camera system, for example, may pick up the location marks tocalibrate the navigation system and the control system. Various otherreference elements such as physically defined lines, such as found onroads or parking lots may be a type of navigation control system. Stillfurther examples may involve the embedding of conductive wires to createa navigation information system. A grid of such conductive wires maycreate a calibrated work floor with a good deal of accuracy. In stillfurther examples, the surface to be acted on by the mobile additivemanufacturing apparatus may be a temporary surface that may itself bemoved. Sheets of a temporary material may function as the surface andthese sheets as well may include coloration and/or physical elementssuch as embedded conductors to provide a telemetry signal for thenavigation element.

The Navigation, Control and Sensing system 130 may function to define apath that the mobile additive manufacturing apparatus follows in itsprocess. In other examples, the path itself may be figured into thedesign of a desired topography. For example, in some examples it may benecessary for the mobile additive manufacturing apparatus (Addibot) totravel along a road surface and perform additive manufacturing based onaspects that it measures or determines of the surface as it travels. Inother examples, the shape of a feature to be deposited across a surfacemay involve the control of the navigation system to move the Addibot toa location where the additive manufacturing element can further controlthe additive process. In these cases, the path of the Addibot could bearbitrarily complex based on a model that it follows to generate an endresult.

The Navigation, Control and Sensing system 130 may include aspects ofartificial intelligence such as algorithms to process and use sensingdata by machine based learning and other artificial intelligenceprotocols. Hardware including processing units may be customized indesign for artificial intelligence-based processing. The vision systemin particular may be directly coupled with customized artificialintelligence-based processing equipment including artificialintelligence algorithms. Referring to FIG. 1C, an exemplary structure ofan artificial based processing system or algorithm which may beimplemented in both software and hardware is illustrated in concert withother components of an Addibot 101C.

In some examples, the artificial intelligence processing system 102C maybe incorporated within the navigation, control, and sensing system 130Cor as illustrated it may work in concert with the navigation, control,and sensing system 130C routing data along a bus between the controllersin the navigation, control, and sensing system 130C and the artificialintelligence processing system 102C. In such an example the data flowswithin the mobile additive manufacturing system 103C-107C may be routedthrough the artificial intelligence processing system 102C asillustrated or there may be parallel systems which route the data inparallel to the standard navigation, control, and sensing system 130C aswell as the artificial intelligence processing system 102C. The natureof data flow and signal feedback between an artificial intelligenceprocessing system 102C create new examples of the mobile additivemanufacturing system architecture with new aspects of drive system 120C,navigation, control, and sensing system 130C, additive manufacturingelement 140C, material storage system 150C, vision system 160C, andcommunication system 180C. Each of these systems may perform differentlyin concert with an artificial intelligence processing system 102C.

For example, a vision system 160C tied to an artificial intelligenceprocessing system 102C may use various machine learning and artificialintelligence algorithms, hardware structures and the like to improveeffectiveness in various aspects of vision system performance. Trainedartificial intelligence processing systems may recognize defects,structures, and other aspects of a surface such as a roadway that willbe processed with additive manufacturing. The system may have as anequivalent to “motion decoding” specific interlocking of both an alterednavigation, control, and sensing system 130C which may control the drivesystem 120C as well as simultaneous interlocking with an alteredadditive manufacturing element 140C. The system may also interlock withaspects of the vision system 160C where the vision system inspects theresult of the additive manufacturing process and provides learningfeedback which may trigger aspects of reward evaluation in theartificial intelligence system and foster improved “learning” of thesystem in the field and “on the fly”.

Referring now again to FIG. 1A, an additive manufacturing element 140may be represented. The various techniques known in the art may beincluded as an additive manufacturing element including, for example,extrusion heads, stereolithography processing heads and materialprinting heads. An altered version of stereolithography may occur by theapplication of thin films of liquid material upon the surface which isthen subsequently processed to create hardened surfaces. If theunreacted material is removed a subsequent application of liquidreactant can begin to build the next layer.

The material printing heads may have a wide diversity incharacteristics. Printing heads with very fine resolution may beutilized. In other examples larger volumes of material may be printedwith heads that have gross resolution. As an example, a printing headmay have rows of print heads that have an orifice size such that aroughly millimeter sized droplet may be formed. Such a droplet may havea volume of roughly 10-100,000 times that of a droplet from a 1:1000resolution. The volume of a millimeter diameter droplet may have anestimated volume of about 0.4 microliters.

In some examples, the additive process can relate to an element such asa print head depositing droplet of material over the surface to buildstructure. In stereolithography, an energy source is used to convert theliquid to a solidified material, but in these other examples, thedroplets of material may either react with the surface or solidify byother principals such as by cooling for example. Combinations ofdroplets of different material may also result in reactions that resultin solidified material.

The additive manufacturing element may also function to add materialthat changes color or pattern or other physical properties in selectregions. A version of this type of additive manufacturing may occur whenpowders are deposited in the additive process. The powder may createlines or other demarcations. In some of these examples, a subsequentsealing of the powder form may be deposited by another additivemanufacturing process.

In some examples, the additive manufacturing element may be an energysource such as a laser, ion beam or the like. The energy source may beused to cause liquid material to solidify in defined regions. The liquidmaterial may be added by the Addibot or be present by other means. As anexample, an Addibot may ride upon a transparent surface that may sitabove a liquid reservoir of relatively arbitrary size. An Addibot with alaser may ride upon the transparent surface and irradiate the surfacelayer of the reservoir in desired locations. After a layer is processed,the work material beneath the transparent surface may be moved away fromthe transparent surface by a layer thickness and the Addibot may againmove around on the transparent surface irradiating through the surfaceto image polymerizable material beneath.

The various additive manufacturing elements that may be used in thesemanners comprise the art that is consistent with mobile automatedadditive manufacturing.

An additive manufacturing element 140 may be part of the mobile additivemanufacturing system. There may be numerous types of additivemanufacturing elements consistent with this type of system. For example,in some examples, the material to be added may be found in a liquid formeither in its nascent form or in a processed form. The liquid materialmay be processed by droplet ejection printing schemes. Some printingelements may be comprised of MEMS jet printing elements. In otherexamples, the printing element may be composed of an array of valvesthat open and close to dispense controlled amounts of the liquid. Instill further examples, a liquid stream may be controlled by thepresence of mechanical shunts which do not allow a stream of the liquidto be released below the element. In fact, any liquid control mechanism,typically deployed in an array of elements, which may allow for aspatial control over the dispensing of the material, may comprise anadditive manufacturing element for liquids in a mobile additivemanufacturing system.

For the purposes of seal coating, painting and generalized materialdispensing on a surface, the additive manufacturing system may beconfigured with a rotatable spray head system with various spray headson a supporting bar or other holding shape that can be rotated around acentral point. Referring to FIG. 1D, an exemplary rotating spray system101D is illustrated. A rotational gantry 102D may provide for bothrotational motion and the coupling of material feed systems through arotary gland that may also feed electrical signals, compressed air,vacuum, and the like. The system may have numerous spray dispensingnozzles, which in this case are illustrated by nozzles 103D, 104D and105D. More dispensing nozzles or fewer may be employed.

An alternative example may be found by referring to FIG. 1E, where anexemplary rotary dispensing system is illustrated. A squeegee basedrotary system 101E is illustrated with an associated rotary gantry 102Ethat may also include function for physical rotary motion as well asfacilities to pass materials, signals, vacuum, and gas through therotary process. In the examples, three dispensing heads 103E, 104E and105E may spray or drip material onto the surface while rotary blade or“squeegee” type elements 106E and 107E may move the material in a rotaryfashion. The rotary system may have a split in the center which is whythere are two squeegee type elements 106 and 107E which may drag indifferent directions due to the rotary motion. The blades may be solidstructures as illustrated or may be split with multiple blade fingersinterfacing with the surface. In some examples a cavity within thesqueegee blade may be used to dispense material between the bladefingers and onto the surface. There may be sensors located within thecavity to measure amounts of material and other aspects of the materialincluding temperature. These sensors may generally be located on bothillustrated systems in FIGS. 1D and 1E. Components from these systemssuch as the spray heads, drip heads, squeegee blades, sensors may bemade to be easily replaceable, and in some examples the entire rotaryarm may be replaceable.

Referring again to FIG. 1A, a material storage system 150 may be found.As has been described there may be numerous types and forms of materialthat may be processed by an Addibot. In some examples, materials infilament form may be used; in other examples liquids of various kindsmay be employed. And, in still further examples, solids such as powderform materials may be utilized. In each of these cases, there may benumerous material options within a particular kind. There may bestandard ABS plastic filaments or other plastic filaments. In someexamples, other fibers such as fiber class filaments may be utilized incomposite processing such as with epoxy resin combinations withfiberglass filaments. In the liquid form a great diversity of materialsmay be used including resins, photoactive and thermos-active materials.Other materials in the liquid form may be a solid at an ambientcondition but may be processed by the additive manufacturing system atconditions that make the material liquid. The powder form examples maybe thermo-active and photoactive materials or alternatively may bematerials that in combination with other deposited materials cause areaction to occur resulting in a deposited solid material. In the stateof the art, metals, insulators, and ceramics to name a few materials maybe formed by the processing of powder form materials. In other examples,the powder deposited will remain in a powder form on the surface.

In the various materials examples that may be possible with an Addibot,the environmental storage conditions on the Addibot may be important.Accordingly, the material storage system 150 may have controls overnumerous environmental conditions such as the temperature of thematerial storage, the pressure, the ambient gasses or a vacuum conditionand the humidity to mention some examples. Thus, the material storagesystem for an Addibot would have control systems for the importantenvironmental conditions. The storage system would need to allow for theautomated or non-automated replenishment or replacement of the materialthat is located in an Addibot. In some examples various combinations ofmultiple material storage systems may be present. For example, a powderstorage system and an additive manufacturing element for powder formsmay be combined with a liquid storage system and an additivemanufacturing element for liquid forms upon the same Addibot system. Instill further alternative, two different forms of material may becombined with different storage systems that feed a single additivemanufacturing element that is designed to simultaneously process the twomaterial types.

Other examples may have additive manufacturing elements to dispersesolids. The element may extrude elements of material that may be gelledto allow for the material to be formed by the additive manufacturinghead. The extrusion elements may also deposit small pieces of extrudedmaterial that is in a gelled or partially melted form. Lasers or otherhigh energy sources may cut the small pieces from the extrusion printhead as it is being extruded. In other examples, the material is not cutas it is formed into three dimensional shapes. The material storagesystem may store and process pavement sealant. In some examples,pavement sealant may be continuously filtered and circulated from thestorage element through a pumping element. During use some of the pumpedsealant may be distributed.

The various materials that are added to the surface may be furthertreated to form a solidified surface. In some cases, materials may betreated with light or other energy to heat or otherwise react thematerials to form a solidified result. In other cases, a chemicalreaction may be caused to occur by the addition of a second material. Insuch cases the additive manufacturing element may be comprised ofcontrol elements to disperse liquids and solids or multiple liquids. Inaddition, the system may include the elements to post process thematerial such as by thermal or photochemical action. These postprocessing elements may be located on the additive manufacturing elementor may be located in other portions of the system. In some examples, thepost processing may also include processes to wash or clear the surfacefrom materials that are not solidified, adhered, or attached to thesurface. These processes may include processing to remove solid, powderor liquid material remaining on the work surface such as vacuuming orsweeping. The removed material may be recycled into the material storagesystem or may be moved to a waste receptacle. In similar fashion thepost processing steps to remove material may be performed by elementsthat are included on the additive manufacturing element or additionallybe other elements that are included in the mobile additive manufacturingsystem.

The results of the various additive processes may be measured by variousmanners to verify the conformity of the result to a modeled surfacetopography. An inspection system or a vision system 160 may performthese measurements to control the results. In some examples, the surfacemay also be studied with a similar or identical metrology element todetermine the presence of topography. Another way of looking at such ameasurement before the additive manufacturing step may be to examine thesurface for defects, cracks or fissures that may need to be processed toform a flat surface for example. Therefore, the vision system 160 may infact occur multiple times in the system. A pre-measurement may beperformed by a first measurement element and a post processingmeasurement may be performed by a second measurement element. There maybe numerous manners to measure the surface topography. As an example, alight or laser-based metrology system may scan the surface and analyzethe angle of reflected or scattered light to determine topography.Similar scanning systems based on other incident energy like sound orelectromagnetic signals outside the visible spectrum like infrared or UVradiation, for example, may be used.

A different type of metrology system may result from profilometry wherean array of sensing elements may be pulled across the surface and bedeflected by moving over changes in topography of the surface. An arrayof deflecting needles or stylus may be dragged over the surface. In analternative example, a pressure sensitive surface may be pulled over thesurface under study.

The surface that the mobile automated additive manufacturing system actson may have movable defects that exist on it. This may be commonlyclassified as dust or dirt for example. An element for preparation ofthe surface 170 may be located in an Addibot. In some cases, thematerial may be removed by a sweeping or vacuuming process that movesthe particles into a region that removes them from the surface. Othermethods of removal, which may replace or supplement the sweeping orvacuuming, may include pressurized gas processing which may “blow” thesurfaces clean. There may also be electrostatic processes which chargethe particles with electric charges and subsequently attract them tocharged plates which attract the particles away. A cleansing process mayalso comprise a solvent based cleaning process which may subsequently beremoved in manners mentioned earlier, in a combination of the Addibottechniques. A first Addibot may function to pretreat a surface in avariety of manners while a second Addibot performs a topography alteringadditive manufacturing process.

Another element, a communication system 180, of the mobile additivemanufacturing system may be found referring to FIG. 1. In general,Addibots may be used in combinations to perform functions. Toeffectively perform their function, it may be important that theAddibots may be able to communicate with each other. The communicationsystem may also be useful for communication between the Addibot and afixed communication system. The fixed communication system may be usefulfor communicating various data to the Addibot as well as receiving datatransmissions from the Addibot. The data transferred to the Addibot mayinclude programming software or environmental target files or the datamay include environmental data such as mapping data or topological dataas examples. The communication may be carried by RF transmissionprotocols of various kinds including cellular protocols, Bluetoothprotocols and other RF communication protocols. The communication mayalso utilize other means of data transfer including transmissions ofother electromagnetic frequencies such as infrared and opticaltransmissions. Sound waves may be useful for both communication andspatial mapping of the environment of the Addibot. In some examples theAddibot may be tethered to at least a communication wire that may beuseful for data transmission.

Another form of communication may relate to visual based informationconveyed by the Addibot body itself. In some examples, the Addibot bodymay include a display screen to communicate information to thesurroundings in the form of graphic or visual data. As an example, thedisplay can warn people in the environment of the Addibot as to thefunction that the Addibot is performing and when and to where it maymove. Audio signaling may comprise part of the communication system inaddition. As well, the Addibot may be configured with a light systemthat can project visual signals such as laser patterns, for example.

The communication system may be useful to allow external operators toprovide direction to the Addibot. The directions may include the controlof navigation in both a real time and a projective sense. Users mayutilize the communication system to provide activation and deactivationsignals. Numerous other functional control aspects may be communicatedto control operation of the Addibot other than just the transfer ofsoftware programs including for example activation and control of thevarious subsystems.

A Power and Energy storage element 190 may be found within the mobileadditive manufacturing system. In some examples, an Addibot will betethered with a wire. The wire may be used for a number of purposesincluding providing power to the Addibot drive system or to an energystorage system within the Addibot. In many examples, the Addibot willoperate in a wireless configuration, and therefore, will contain its ownpower system in the mobile platform. Standard combustion engines andhydrocarbon fuels may comprise a power system along with a generatordriven by the engine to charge batteries as an electric charging system.In other examples, a battery powered system may power both the drivesystem with electric motors as well as the electronics and othersystems. The battery storage system may be recharged during periods ofnon-use and the components of such a recharging system may compriseportions of the power and energy storage element. In some examples wherethe Addibot operates in an automated fashion, the recharging of theenergy storage element may also occur in an autonomous fashion whetherit is recharging electrically or obtaining additional fuel stores.

There may be numerous manners to configure the novel mobile additivemanufacturing system that has been described. In the following examples,non-limiting examples are provided as examples of the different mannersthat the Addibot apparatus type may be utilized.

Road Surface Treatment—Sealcoating and Line Painting

One manner that an Addibot may be configured to perform is processingthat observes a local surface topography and adds material to make thesurface flatter, or to replace surface material that has been lost toerosion or other subtractive influences over time. Cracks, fissures,divots, and other local changes to a surface flatness may also beprocessed by adding an appropriate material either to fill in the cracksand fissure or otherwise reshape the surface topography.

Roadway infrastructure includes many surfaces, consisting of a varietyof different materials, that may be subjected to constant eroding orotherwise deteriorating forces that create defects in the surfaces overtime. Some non-limiting examples may include frost-heaving, where waterthat has seeped underneath a road bed or into existing cracks, fissures,or other defects freezes and expands with considerable force, exertingsignificant strain and stress on the surface material; the stress mayeven surpass the allowable stress for the material, creating new defectsin the surface or worsening existing defects. As a destructive process,frost-heaving may be thought of to have a kind of momentum in destroyinga roadway surface—existing cracks form a perfect collection area formore water, which then expands and makes the cracks even larger; thelarger the crack, the easier it is for frost heaving to move morematerial and make the crack larger, eventually forming it into a potholeand possibly creating new cracks. Constant preventive maintenance is astrategy that may be described as counteracting this destructiveprocess' momentum by eliminating the causes of the process (existingdefects where water can collect and contribute to frost-heaving, as anon-limiting example) before they allow the process to build momentum.Large potholes may be not only more susceptible to frost-heaving incertain areas, but also more costly and difficult to repair successfullythan small cracks; since potholes won't form unless there are cracks forthem to form from, if effort is focused on repairing defects when theyare small and manageable, these defects will never form into costlypotholes, and a better quality of road is achieved at lower cost andlower effort than waiting to repair the potholes when they become aproblem for vehicles using the roadway.

One non-limiting example a of constant preventive maintenance processfor roadway surfaces is called sealcoating. With sealcoating, a liquidasphalt emulsion with possible additives like sand grains, as anon-limiting material example, may be sprayed or spread, as non-limitingapplication method examples, onto a roadway surface. The emulsion mayspread into and around cracks and other roadway defects, sealing andrepairing these defects. The applied material also creates a layer ofmaterial on top of the previously existing surface. This may create aflatter surface that is more resilient to wear and tear from vehiclesdriving on the surface, as well as a buffer that adds life to thesurface against forces that remove material from it—these forces mustremove the newly added material first before they can remove materialfrom the structural layers of the roadway. Because sealcoating may bemuch easier and cheaper than processes to repair larger defects or tocreate the roadway itself, utilizing this method regularly can extendthe lifespan of a road at much lower cost than other methods.

Existing sealcoating methods often include numerous processing stepsthat are manually guided by roadway workers. These steps may include, ascommon non-limiting examples, directing a spray wand over the roadwaysurface that sprays the emulsion onto the surface. Another commonnon-limiting example may include directing squeegees or brushes tospread a viscous emulsion evenly over a roadway surface. Because thesemethods are manually directed, they may be directed by a combination ofhuman eyes and hands. Sealcoating processes may be successful inrepairing roadway surfaces by covering the entirety of the road surface,preventing any individual point of the roadway surface from becoming anode for erosion that spreads throughout the rest of the roadwaysurface; manually directed methods for sealcoating may suffer from theinherent imprecision of human eyes and hands, resulting in the failureof an otherwise successful sealcoating operation due to the workersmissing one or a few spots over the entire road surface that formspreading defects and ruin the roadway surface over time. Additionally,since common sealcoating processes may involve countless manual steps,each of which may be tedious, repetitive, and laborious, a workercompleting these steps may inherently fatigue over time, mentally and/orphysically, comprising the quality of their work over time.

Because of these limitations regarding current manually operatedprocessing steps, it may be highly desirable to utilize the precisionand efficacy of Addibots in conducting sealcoating operations. Addibotsconfigured for sealcoating may utilize a combination of computer visionand other possible visual sensors, robotic mobility, and actuatedautomation that replace these possible afore-mentioned manually operatedprocessing steps with significantly improved quality. Repetitiveprocessing steps of the sealcoating operation may also be completed bythe automation and systems combination within the Addibot configured forsealcoating, rather than the human worker who may be directing theoperations of the Addibot in the non-limiting example where the Addibotis directed; an Addibot that may be completing these repetitive stepsmay not fatigue like a human worker may over the course of thesealcoating operation, and thus quality may remain consistentthroughout. There may be numerous additional advantages, beyond what hasbeen already discussed, to using an Addibot configured for sealcoating,that may be discussed below.

Referring to FIGS. 2 and 2B examples of a generic mobile additivemanufacturing system in FIG. 2 item 200 and an exemplary tailoredsealcoating system in FIG. 2B are illustrated. The various components ofFIG. 2 may be included in the system of FIG. 2B and may not beillustrated or visible. Nevertheless, we will discuss the two examplesin tandem. For example, at item 200B an example of an Addibot configuredfor sealcoating may be found. Those systems and aspects that may bepresent in an example of an Addibot configured for sealcoating may bereferred to with their reference from FIG. 2. The chassis 210 of theAddibot may contain and support the systems of the Addibot in a mobileand autonomous manner.

The drive system may have a specific set of embodiments foromnidirectional drive illustrated in FIG. 2B as the drive flexible wheel220B. The depiction in FIG. 2 provides an example of one possible drivesystem 220 using three wheels with a rotating front wheel 225 whereasthe depiction in FIG. 2B depicts a four-wheel example in this case withomnidirectional drive components. An example using different number ortype of wheels may also be within the scope of the inventive art herein.

An alternative non-limiting example of a possible drive system mayinclude an omnidirectional drive system utilizing Mecanum wheels.Mecanum wheels may consist of multiple specialized rollers arranged onspecialized hubs that orient the axis of rotation for each of therollers at 45 degrees with respect to both the plane of the wheel aswell as the axis of rotation of the wheel. As a result, the rollers mayindividually rotate as the wheel spins; by coordinating the relativerotation speeds and directions of each of the four individual Mecanumwheels, different directions of linear or rotational movement may beachieved with high precision. This may include linear movement at any ormany possible angles with respect to the center of mass of theapparatus. This may also include turning with no turning radius,allowing for full rotational orientation of the apparatus at any angleof rotation with respect to the center of mass of the apparatus. Ifthese two characteristics are combined in a drive system, the exemplarydrive system may be able to move in a particular linear path over asurface while, at the same time, changing its rotational orientation.

The drive system may be constructed, though, in a manner in which itdoes not interact with the other Addibot systems, for example, thevision system or the additive manufacturing element system. Depending onhow the wheels of the drive system are powered, they may also be part ofthe navigation, control, and sensing system. Based on the input from thevision system (as a part of the navigation control and sensing system)the wheels may direct the Addibot to its desired path, in a fashion thatis either autonomous or predetermined, depending on the orientation andnumber of the wheels.

A sensing element 230 may be depicted. This element may be used toperform functions necessary in the navigation, control, and sensingsystem for this example. The navigation functions could be performedthrough GPS, an element grid, or other manners as has been describedrelating Navigation, Control and Sensing system 130 of FIG. 1A.

An additive manufacturing element 240, and a secondary additivemanufacturing element 245 for this example may be shown. The additivemanufacturing element 240, for this example, may be a material printinghead, as described in reference to the additive manufacturing element ofFIG. 1A, which may dispense droplets of sealcoat emulsion of acontrolled size, as well as a controlled temperature (which may becontrolled by the material storage systems). This element may functionto execute a precise additive process of the material, based on inputfrom the vision system. Another element, in this example, the secondaryadditive manufacturing element 245 may be a roller or other type ofdistribution apparatus that spreads or smoothens to a degree materialthat was added to the surface. In the alternative example in FIG. 2B,the additive manufacturing system 230B may include a spray bar with asqueegee applicator.

In certain non-limiting examples of an Addibot configured forsealcoating, a distribution system comprising at least an additivemanufacturing element 230B may be fixed to the chassis 210 butpositioned and operant outside of the area between or under thecomponents of the drive system. Utilizing a drive system 220B withMecanum wheels, as a non-limiting example, this distribution system maybe guided in a particular path over a surface that allows thisdistribution system to cover the entire surface it is passing over,without the area between or under the components of the drive systemever passing over any area that was already distributed upon.

Elements of a material storage system 250 of this example are shown.These components may comprise various elements that may be necessary formaterial storage within an Addibot. There may be numerous alternativedesigns and orientations of components that may be consistent with thefunction of an Addibot. In the example of FIG. 2B, a primary materialreservoir 210B where sealcoating emulsion mixtures may be contained, maybe filled by an operator of the Addibot apparatus. Some non-limitingexamples of sealcoating emulsion may include a water-based rubberizedasphalt mixture, a coal-tar based mixture, or acrylic based mixture, allof which may be commonly used in practice for various reasons ofapplicability or environmental conditions. For example, ambienttemperatures, humidity, and sun may allow for a water-based mixture toset well on a certain driveway, which may make it preferable to othermixtures for which the typical of conventional application methods mightbe more difficult or imprecise. These different non-limiting examples ofmixtures may also comprise different additives that contribute to addedabrasion resistance, improved adhesion, or other desired aspects. Somenon-limiting examples of commonly used additives may include sand orother finely ground stone aggregates, polymers or other syntheticmaterials, coloring chemicals, among others.

Recirculation of sealcoating emulsion during the surface preparation mayalso be directed to the primary reservoir. Typical sealcoating emulsionsmay comprise mixtures of many different materials. Over time, if theyare not mixing or moving through a processing/application system, thesemixtures may settle and separate into layers of their discretecomponents. Naturally, it may be desirable for an emulsion mixture to bewell-mixed so that the applied material consists of a uniform mixture ofall the materials in the sealcoating emulsion. To achieve this mixing, amaterial storage system 250 may have pumps or other components thatcycle material through the system at pressure, to mix the material.Typically, two or more cycles through the material storage system 250may be enough for standard-grade sealcoating emulsions, but otherparameters may be defined for what is considered adequate mixing of thesealcoating emulsion. Physical mixers like an auger, paddles, or othersuch devices may also be used to mix up the sealcoating emulsion used inan Addibot configured for sealcoating. An environmentally controlledsecondary material reservoir may also be used to keep sealcoatingemulsion mixtures at a different storage condition than that used in theprimary storage location, such as the temperature, pressure, or othercharacteristic of the material.

The primary vessel containing the material for dispensing may bereplaceable on the Addibot and the primary material reservoir 210B mayrepresent a bucket of material that in some examples may be procureddirection in that form. In other examples large collections of materialmay be used to fill and refill the primary material reservoir. Inexamples of where the primary material reservoir 210B may be a bucketpurchased in the used form, the interface of the bucket may include asystem which replaces the top of the bucket, or alternatively mayinclude a portion of the bottom of the bucket which may allow forconnection and interface of the material of the bucket to the systems ofthe mobile additive manufacturing system.

A vision system 260 which may be hidden but present in FIG. 2B as well,for this example may be depicted as shown. This element may use avariety of methods such as those described in reference to vision system160 of FIG. 1A. These may include a laser scanner, sensitive extrudingpins or brushes, or such components as may allow for inspection of thesurface to be process or for determination of the topography of thesurface. Alternative orientations may be possible including for examplean orientation where a vision system may be placed behind the additivemanufacturing element to perform a post-inspection of the surface, afterthe material has been applied. Among other purposes, the inspection maybe used to verify the results of the addition process and to see if moreor less material may need to be added.

A surface preparation system 270 for this example may be observed. Inthis example, it may be necessary to remove dust, dirt, asphalt, rocks,or other debris from the road surface before it may impede the accuracyof the vision system in processing the surface topography. The elementsshown in FIG. 2 may include a brushing system, a vacuum system, and ascraping system or a combination of these. These systems may be used toremove undesired particles from the surface. Other particle removalsystems, including ionizing plates, a sweeping broom, or otherbrush-based devices, other types of vacuums or suction devices; highpressure gas or liquid treatments to blow surface debris clear of thesurface or into a collection region, among other systems may also beusable for this example of an Addibot.

A communication system element 280 for this example may be seen. Thiselement may be used to carry out communication processes, either betweenother Addibots or an external user. These tasks may be carried out inmanners consistent with methods described in reference to thecommunication system 180 of FIG. 1A.

A power and energy storage system 290 may be depicted. This element maybe a battery to power the example's electrical systems and motors, or acombustion engine to power the drive system which may also charge abattery system as non-limiting examples. The power system may providemechanical energy to the drive system or may provide electrical energyto the drive system which may power engines that comprise portions ofthe drive system. Electrical energy from generators connected tocombustion engines or from battery sources may be used to powersubstantially all of the electronic systems utilized throughout anAddibot. Other energy storage sources such as compressed air may alsocomprise acceptable solutions for energizing the operations of anAddibot.

Some or all of the elements illustrated in FIG. 2 may be present in thesystems of the example of FIG. 2B.

Communication to the control systems may be performed by wirelesscommunication protocols such as Wi-Fi, Bluetooth, cellular communicationprotocols such as gsm, CDMA for example, and operate on differentcommunication channels and frequencies as have been discussed.Additionally, Addibots of various types may also comprise connectionsfor wired communication and also display screens and input/outputdevices to allow operators to provide control signals, data transmissionand other interaction with the Addibot.

The various systems of Addibots may necessarily utilize materials orother commodities such as energy during the course of processing. Thematerial storage systems may interact with fixed units that may refillthem, or they may be filled by operators in a manual fashion. In theexample of a sealcoating Addibot the material storage system may berefilled with sealcoat emulsion for example.

In examples that utilize batteries as a power source, the batteries maybe powered at a charging station. The interaction of the Addibot with acharging station may be performed in an autonomous fashion where theAddibot moves itself into a proper location to interface with thecharging station. Alternatively, an operator may interact with theAddibot and connect it with a charging system.

Control Systems

Referring now to FIG. 3, a controller 300 is illustrated that may beused in some examples of a mobile additive manufacturing apparatus. Thecontroller 300 includes a processor 310, which may include one or moreprocessor components. The processor may be coupled to a communicationdevice 320.

The processor 310 may also be in communication with a storage device330. The storage device 330 may comprise a number of appropriateinformation storage device types, including combinations of magneticstorage devices including hard disk drives, optical storage devices,and/or semiconductor memory devices such as Flash memory devices, RandomAccess Memory (RAM) devices and Read Only Memory (ROM) devices.

At 330, the storage device 330 may store a program 340 which may beuseful for controlling the processor 310. The processor 310 performsinstructions of the program 340 which may affect numerous algorithmicprocesses and thereby operates in accordance with mobile additivemanufacturing equipment. The storage device 330 can also store Addibotrelated data in one or more databases 350, 360. The databases 350,360may include specific control logic for controlling the deposition ofmaterial at each of the additive manufacturing components which may beorganized in matrices, arrays, or other collections to form a portion ofan additive manufacturing system.

As mentioned in reference to FIG. 1D, an Addibot may benefit fromoperational incorporation of artificial Intelligence, machine learningand other such operational control aspects. In some examples, thehardware as depicted in FIG. 3 may include hardware and software aspectsthat support artificial intelligence including as non-limiting examplesprocessors specifically designed to optimize performance of artificialintelligence algorithms, data bus designs to optimize performancebetween various blocks such as the vision system and controller andassociated algorithms.

While the disclosure has been described in conjunction with specificexamples, it is evident that many alternatives, modifications, andvariations will be apparent to those skilled in the art in light of theforegoing description. Accordingly, this description is intended toembrace all such alternatives, modifications and variations as fallwithin its spirit and scope.

Methods

There may be numerous methods of utilizing an Addibot, manufacturing anAddibot or creating a product with an Addibot. Referring to FIG. 4, anexemplary set of method steps that may be commonly utilized in numerousexamples of Addibots are displayed. The steps are displayed in a flowchart for example. The steps may flexibly be used or not used, and theorder of the steps may be changed within the scope of the inventive artof Addibots.

At step 410, an Addibot of a particular type may be obtained by a user.Next, at step 420 the user may transmit a control signal to the Addibot.The transmitting may involve numerous means including a wirelesstransmission, a wired transmission or a transmission involving aphysical interaction such as pushing a switch or a display panel of anAddibot. The initiation signal may cause a variety of responses that areproximately caused by the initiation even if further interaction withthe user is or is not required or if the Addibot will flexibly respondto its environment or programming thereafter.

At 430, in some examples the Addibot may perform an orientation step.This step may assess one or more of determining a spatial location in aspatial coordinate system and may also assess movement and direction ofmovement or potential movement in a spatial coordinate system. In someexamples, the step may be performed by activating an omnidirectionaldrive system. This step may include many of the different aspects ashave been discussed herein.

At 440, in some examples the Addibot may perform a metrology process ona region of a surface. In other examples at 440 an apparatus external toan Addibot may perform a metrology process on a region of a surface andmay communicate information to an Addibot related to the metrology orrelated to the processing of the metrology data 450 in some form.

Additionally, at 450, in some examples the Addibot may process theresult of the metrology by means of a processor. In some examples, thesaid process may be one as described in FIG. 3.

At 455 in some examples an optional step may involve planning the pathof the mobile additive manufacturing apparatus for movement with anomnidirectional drive system. In some examples, the path planning mayuse hardware and/or software for artificial intelligence or machinelearning processing.

At 460, in some examples the Addibot will utilize the information thatit has received in various manners about the surface and any desiredmodel that results from this information and based on a digital modelprovide controlling signals to the additive manufacturing system.

At 470, in some examples, the Addibot will deposit a first layer ofmaterial on a surface. The Addibot may be oriented, in some examples,with a drive system that operates as an omnidirectional drive system. Insome example the path that the omnidirectional drive system performs mayallow the Addibot to deposit while not passing over previous deposits.In some examples, the drive system may perform the ability to not passover previous deposits with continuous steps which do not reversedirection of the Addibot during the path progression. Continuing at step470, in some examples, the Addibot will deposit a first layer ofmaterial on a surface. In some examples, the first layer of materialwill be comprised of adhesives or sealers. In some other examples, thefirst layer of material may be comprised of a mixture of aggregate orsmall solids and an adhesive or sealing agent. In still furtherexamples, the adhesive or sealing agent may be further processed byexposure to an energy source such as a UV light exposure to initial apolymerization reaction in the material.

At 435, there may be a loop process that occurs in some examples andunder some situations that may cause the Addibot to return to step 430and continue processing. Alternative, in some examples, as shown at step445 a loop process may occur that may cause the Addibot to return tostep 440 and continue processing.

At 480, a step may occur where the Addibot is moved from a firstlocation to a second location. In some examples, a characteristics ofthis movement is that as part of the Addibot moving the additivemanufacturing system as a whole moves from a first location to a secondlocation even if portions of the additive manufacturing system couldmove some or all of the printing head or other additive element to thesame second location without a movement of the Addibot.

At step 490, the Addibot may deposit at the second location a secondlayer of material. The nature of the second deposit may comprise adifferent material, or a same material. The nature of the second depositmay comprise a different physical characteristic such as thickness orthe same characteristic as a first deposit. The second deposit may becontiguous with a first deposit but be located at a second location andbe considered a second deposit, by the very nature of being at a secondlocation.

At step 435, there may be a loop process that occurs in some examplesand under some situations that may cause the Addibot to return to step430 and continue processing. In an alternative example, in someexamples, as shown at step 445 a loop process may occur that may causethe Addibot to return to step 440 and continue processing.

Referring to FIG. 4B, an Addibot of a particular type may be obtained410B by a user. Next, at step 420B the user may transmit a controlsignal to the Addibot. The transmitting may involve numerous meansincluding a wireless transmission, a wired transmission or atransmission involving a physical interaction such as pushing a switchor a display panel of an Addibot. The initiation signal may cause avariety of responses that are proximately caused by the initiation evenif further interaction with the user is or is not required or if theAddibot will flexibly respond to its environment or programmingthereafter.

At 430B, in some examples the Addibot may perform an orientation step.This step may assess one or more of determining a spatial location in aspatial coordinate system and may also assess movement and direction ofmovement or potential movement in a spatial coordinate system. In someexamples, the step may be performed by activating an omnidirectionaldrive system. This step may include many of the different aspects ashave been discussed herein.

At 440B, in some examples the Addibot may perform a metrology process ona region of a surface. In other examples at 440B an apparatus externalto an Addibot may perform a metrology process on a region of a surfaceand may communicate information to an Addibot related to the metrologyor related to the processing of the metrology data in some form 450B. Insome examples, these metrology steps may involve the measurement ofsurface topography in such a manner as to allow for the adjustment ofthe level of a forming mold as it is placed to interact with thesurface.

Additionally, at 450B, in some examples the Addibot may process theresult of the metrology by means of a processor. The processor may insome examples identify the level of the surface. In other examples theprocessor may identify the presence of a crack or other defect,determine a need for such a feature to be filled or otherwise haveaction performed on it, and then establish the location information forthe feature detected. In some examples, the detection of a defect maycause the Addibot to send a signal and wait for a user to interact withthe Addibot for additional controls.

At 455B in some examples an optional step may involve planning the pathof the mobile additive manufacturing apparatus for movement with anomnidirectional drive system. In some examples, the path planning mayuse hardware and/or software for artificial intelligence or machinelearning processing.

At step 460B, in some examples the Addibot will utilize the informationthat it has received in various manners about the surface and anydesired model that results from this information and based on a digitalmodel provide controlling signals to the additive manufacturing system.The controlling signals may cause the Addibot to adjust the level ofcomponents within the Addibot; or the level of the Addibot frame itself.

At step 470B, in some examples, the Addibot may create a first structureby extruding material into a forming mold. In some examples, the firstlayer of material will be comprised of thermoplastics or other extrusionmaterials. In some examples, the Addibot may fill a portion of theresulting formed structure with wall forming materials such as cement.In other examples, the Addibot may signal the completion of a firststructure formation and another device or another Addibot may add wallforming materials to the thus formed structure.

At step 435B, there may be a loop process that occurs in some examplesand under some situations that may cause the Addibot to return to step430B and continue processing. In an alternative example, in someexamples, as shown at step 445B a loop process may occur that may causethe Addibot to return to step 440B and continue processing.

At step 480B, a step may occur where the Addibot is moved from a firstlocation to a second location. In some examples, a characteristic ofthis movement is that as part of the Addibot moving the additivemanufacturing system as a whole moves from a first location to a secondlocation even if portions of the additive manufacturing system couldmove some or all of the printing head or other additive element to thesame second location without a movement of the Addibot. Forming moldpieces that may be present in the Addibot may be moved verticallyupwards and downwards in the process of readying the Addibot formovement and then preparing the Addibot for a next processing step. TheAddibot may be oriented, in some examples, with a drive system thatoperates as an omnidirectional drive system. In some example the paththat the omnidirectional drive system performs may allow the Addibot todeposit while not passing over previous deposits. In some examples, thedrive system may perform the ability to not pass over previous depositswith continuous steps which do not reverse direction of the Addibotduring the path progression.

At step 490B, the Addibot may create a second structure by extrudingmaterial into a forming mold at the second location. The nature of thesecond structure formed may comprise a different material, or a samematerial. The nature of the second structure formed may comprise adifferent physical characteristic such as thickness or the samecharacteristic as a first deposit. The second structure formed may becontiguous with a first structure formed but be located at a secondlocation and be considered a second structure, by the very nature ofbeing at a second location.

Teams of Mobile Additive Manufacturing Systems

In the performance of sealcoating as a non-limiting example, the rate atwhich the road surface is processed may be complemented by the concertedprocessing of multiple Addibots. Referring to FIG. 5 item 500, in someexamples, a team of two or more Addibots 510, 511, and 513-515, mayprocess the road surface. In these cases, the Addibots may need toaccurately communicate and sense the presence of other Addibots. In someof these examples, the concerted action may also involve processing byan external processing or controlling device 550 that communicates withand to the Addibots. Proximity sensors in the communication or othersensing components may operate as well to establish the presence ofobstacles such as other Addibots or humans or other such obstacles thatmay be present on a road surface. Depending on the maximum amount ofmaterial desired for storage on one Addibot at one time, desires tolimit the size or discrete throughput of an individual Addibot, or otherpossible design considerations that might determine the maximumthroughput of an Addibot configured for sealcoating, as non-limitingexamples, an Addibot may not be able to achieve a throughput to completea certain sealcoating job in a satisfactory amount of time. Utilizingmultiple Addibots configured at a certain throughput may increase theoverall throughput by a factor for each Addibot used; two Addibots maycomplete the job in half the time, three Addibots may complete the jobin a third of the time, etc. Teamwork of multiple Addibots may alsoallow for fewer processing inefficiencies, to streamline progress of asealcoating job. As a non-limiting example, if an Addibot needs torefill the storage tank of its material storage system, a second Addibotmay continue sealcoating while the first Addibot refills its storagetank; the first Addibot may then continue sealcoating, working while thesecond Addibot subsequently refills its storage tank. Alternatively, aspecialized robotic device 540 may function to fill the Addibots withmaterial from a storage tank on the controlling device 550. There may benumerous manners that teams of Addibots may function to sealcoat andline paint a roadway surface or perform other coordinated additivemanufacturing processing.

Advanced Roadway Construction with Addibots

Examples of structure building with extrusion components within anAddibot have been described in the recent section. Different versions ofextrusion components may be used to construct advanced roadways as well.The use of the term roadway in this disclosure is intended to embrace aninclusive definition as may be standard in the industry wherein aroadway includes the lanes for vehicular traffic, the shoulders alongthose lanes, medians between on-coming lanes, turning lanes, and marginsalong the shoulders to separate the roadway from its surroundings.

Referring to FIG. 6, some features that may be produced by an Addibotconfigured to support roadway construction may be observed. A roadway610 may be formed in the various standard manners that such surfaces areconstructed. There may be an interface, where a roadway according to thepresent disclosure has an advanced formed base with a filled bedmaterial. Thereafter, Addibots may extrude various structural features.Various interfaces in a such a construction process may create seamsthat are expressed at the surface of the roadway. A mobile additivemanufacturing system may coat the seams in manners as have beendescribed. Furthermore, the coated surfaces may be painted in mannersusing the type of systems as have been described herein. In someexamples the mentioned spray nozzles may be configured to dispensepaint.

As an example, some roadway designs require the possibility for aroadway to expand under heat with expansion joints or other expansionelements. In some examples, an Addibot may extrude a feature at alocation along the roadway surface. The location of the feature may bepresent in a model of the roadway that exists in Addibots andcontrolling apparatus for an Addibot or combinations of Addibots. Theextruded feature may, as an example, be a channel that is formed at thefull height or nearly the full height of the roadway bed when theroadway is completed. In some examples, the channel may be filled with amaterial and a subsequent process may seal the feature.

Addibots may be used to extrude or spray supporting meshes of variouskinds, shapes, and designs. In some examples a dispensed pattern may bea cross-hatch pattern. A cross-hatch pattern according to thisdisclosure is a pattern where two or more features of the patternapproximate intersecting lines. In other examples a unit cell pattern,where a unit cell pattern means a pattern where portions of the patternare repeated, a beehive pattern or various other patterns that could beuseful in supporting a roadbed under the various stresses that it isexposed to. In some examples, the extruded or sprayed material may be acomposite of molten material with embedded fibers, nanofibers,nanotubes, and other materials which may increase strength, flexibility,ability to stretch and other material characteristics that may bedesirable for a supporting material which may be embedded in a roadbed.In some examples, the bed of the roadway may be comprised of asphalt ofa given thickness.

As an example, consider a bed of 16-inch thickness asphalt. In someexamples, the extruded supporting material may be a full six-inchthickness, a portion of the six inches, or in some examples, the roadwaymay be formed in multiple levels each one having another extruded layer.In some examples, the extruded material may be formulated withsupporting material embedded within where the molten material may bechosen to fully or partially mix into the hot asphalt as it is laid. Apartial melt of the material may leave a strengthening pattern offibers, nanotubes and the like within the roadway yet not createsignificant gaps within the roadway bed.

Another feature that may be added to the roadway surface may be achannel that may be used to embed materials such as conductive materialwithin a roadway. There may be numerous uses for embedded conductivematerial including sensing of various kind, communication interfacethrough wireless means and communication routing along the roadway. Thechannel may route electrical connections along a roadway and may alsoroute them to the side of the roadway at a side channel. The resultingdeposits may create features which can be sealed and or paintedsubsequently.

The channel may contain electrically conductive material with othermaterials as well. In some examples, the channel may containcommunication devices such as optical fiber. The optical fiber may routesignals along the roadway as well as to devices along or embedded withinthe roadway. The channel may be filed with insulating materials ofvarious kinds and in some examples, portions of the channel may also maybe topped with structures that act as antenna. In some other examples,the channel may be layered with different layers of materials, some ofthe layer may contain and insulate metallic wires, optical fiber, andother such active components.

Referring again to FIG. 6 an advanced roadway 610 in conjunction with anAddibot 630 is depicted. In some examples, an advanced roadway may havebeen formed with use of Addibots in a manner as described. The roadwaymay be formed with embedded sensors, antennas, or other devices forfacilitating communication 631 between an Addibot 630 and the advancedroadway 610. In forming the advanced roadway, a generic Addibot 630 mayutilize an omnidirectional drive system, such as Mecanum wheels as anon-limiting example. In utilizing such an omnidirectional drive system,may benefits with regards to orientation of the Addibot and its materialdistribution systems, navigating the Addibot 630 with precise linear androtational control, among many others, may be achieved. Within theadvanced roadway 610 may be communication devices 632 that may be buriedwithin the roadway, the shoulder or the side of the roadway or be uponthese locations. In some examples, there may be communication devices onroadway poles, signs, and the like. The communication 631 may comprisewireless communication and may involve radio frequency, infraredfrequency, optical frequency, or other forms of wireless communication.In some examples, the advanced roadway may be formed with embeddedfibers 635 formed of conductive materials or optical fiber. The embeddedfibers 635 may also be considered wires. There may be connection ofwires 638 to power sources along the roadway. The power sources may bestandalone sources such as solar panels 637 or be connected to powertransmission grids 639.

Communication signals may be routed through the advanced roadway andshoulders of roadways as depicted in FIG. 6. In some examples, thecommunication signals may be routed out of the roadway to a wirelesstransmitter 633 located along the roadway. In some examples, signals maybe transmitted from one wireless transmitter 633 to another transmitter636. A combination of transmission through conduits in the roadbed andto roadside transmitters may be used to transmit signals of variouskinds. In some examples the signals may relate to the movement oftraffic along the roadway. The signals may also relate to conditionsalong the roadway as detected by sensors or traffic itself. In otherexamples the signals may involve communication signals unrelated to thetraffic and may be standard communications that are routed alongroadways. The signals from the roadside communication transmitters suchas wireless transmitter 633 may be routed to neighboring structures 634such as residences or businesses. The transmissions in some examples maycomprise standard internet communication transmissions, or in otherexamples the signals may relate to traffic flow along the roadway.Autonomous vehicles may use the various communications and sensorpathways as part of technological support of the traffic flow. Signalsfrom traffic may be routed from vehicle to vehicle with the support ofthe roadway communication system. And, signals from traffic may berouted along wireless pathways to internet connections to centralcontrollers for traffic flow that may be located at off road sites suchas neighboring structures 634. The internet connections may be used totransmit signals from and to remote control systems. The resultingconstructed structure may subsequently be processed by an application ofseal coating and or painting.

In an example related to FIG. 6, the communication and control systemsmay be used to control repair of advanced roadways. Addibot 630, may beguided to regions that need repair of various types. The need for repairmay be detected in various manners such as for example sensors or imagecapture devices on traffic vehicles, control information provided byhuman inspectors or roadway users or the like. In another use of thecommunication infrastructure of the exemplary advanced roadway system,the Addibot can also receive location information from the informationand communication systems of the advanced roadway.

Today's advanced roadways are increasingly being used to supportvehicles with increasing degrees of autonomation. Some of the basicsystems rely heavily upon the ability to detect lineage of the roadwaysystem, which in some examples may also be in conjunction with imbeddedcommunication systems.

Referring to FIG. 7, an illustration of exemplary defects that may berepaired with systems operating with advanced drive systems for a repairof a roadway 710 is illustrated. Cracks 720 of various types may occurin a roadway surface. There may be numerous causes for the formation ofcracks; but after a crack forms it can grow and generate more seriousdefects as water may begin to infiltrate the crack. A more seriousdefect may be represented by pothole 730. Here too, there may benumerous causes for the formation of potholes. However, potholes willalso tend to grow over time if they are not repaired. For illustrativepurposes, pothole 730 is illustrated with a level of water within thepothole. These exemplary types of defects and others may be treated bythe utilization of an Addibot.

An Addibot, may be guided to a defect through communication of locationinformation. In other examples, an Addibot may analyze a road surface todetect the presence of cracks or potholes in a non-limiting example.Teams of Addibots may survey roads and repair the defects that arefound. Examples have been provided for the repair of potholes inconjunction with advanced roadways, it may be apparent that Addibots maybe used in similar manners for repair of such features on genericroadways of various types.

The exemplary Addibot as has been described earlier in the presentdisclosure may be used to perform a process of repair, and referring toFIG. 8A, a repair on a pothole 800 may be illustrated. An exemplary stepfor drying the pothole 805 defect may start with a vacuum process or theaddition of a drying agent followed by its removal. Next fillingmaterial may be added to the pothole. In an example, a compositematerial 815 of filler and adhesive/sealing material may be added inaddition step 810.

In another example of an addition step 820, a layer of filler material825 such as stone may be added as an example. An addition step 830 mayadd a layer of adhesive and sealing material 835 upon the layerdeposited in the addition step 820. In some examples, the addition step820 and addition step 830 may be performed and then repeated in sequencenumerous times until the pothole 800 is filled to an appropriate level.In some examples, the appropriate fill level may be to the top of thepothole 800 to be level with the surrounding roadway. In other examplesthe appropriate fill level may be above the level of the surroundingroadway.

In some examples, the filed pothole 800 may be further processed byprocessing after filling 840. The processing after filling may includerolling or other high-pressure treatments to consolidate the filledmaterial. In other examples, treatments with polymerizing treatmentssuch as exposure to Ultra-Violet light(UV) may be performed to initiatepolymerization reactions with appropriate polymerizable material if itwas included in the adding of a layer of adhesive or sealing materialsteps. In some examples, a cooling treatment 845 may be performed if thefiller material and adhesive and sealing material are added hot orgenerate heat in their polymerization processing. The cooling treatment845 may be performed to cool at least a surface layer of the filledmaterial so that traffic may be allowed to run on the repaired roadway.

The exemplary Addibot as has been described earlier in the presentdisclosure may be used to perform a process of repair, and referring toFIG. 8B, a repair of cracks 850 may be illustrated. An exemplary stepfor cleaning the cracks 855 may start with a cleaning with pressurizedair as a non-limiting example. Next filling material may be added to thecrack. In an example, a sealing agent 865 may be added in addition step860. The Addibot may position a component to perform the addition step860.

In another example of an addition step 870, an array of components maydeposit multiple locations of droplets 875 of sealing material. Thepattern of the multiple droplets may be controlled by a controllerwithin the Addibot. As the Addibot moves over the roadway it maydispense sealing material at appropriate locations based on cracklocation. In some examples, the steps at 860 and 870 may be performedand then repeated in sequence numerous times until the crack 850 at aparticular location is filled to an appropriate level. In some examples,the appropriate fill level may be to the top of the crack 850 to belevel with the surrounding roadway. In other examples the appropriatefill level may be above the level of the surrounding roadway.

In some examples, the filled crack 850 may be further processed byprocessing after filling 880. The processing after filling may includerolling or other high-pressure treatments to consolidate the filledmaterial. In other examples, treatments with polymerizing treatmentssuch as exposure to Ultra-Violet light (UV) may be performed to initiatepolymerization reactions with appropriate polymerizable material if itwas included in the adding of sealing material steps. In some examples,a cooling treatment 885 may be performed if the filler material andadhesive and sealing material are added hot or generate heat in theirpolymerization processing. The cooling treatment 885 may be performed tocool at least a surface layer of the filled material so that traffic maybe allowed to run on the repaired roadway. Examples have been providedfor the repair of cracks in conjunction with discussion of advancedroadway, it may be apparent that Addibots may be used in similar mannersfor repair of such features on generic roadways of various types.

A Mecanum drive system or other omnidirectional drive system may afforda mobile additive manufacturing system greater degrees of freedom toperform additive manufacturing. For example, in a process of crackrepair where the cracks occur across the road surface or are in multiplerut locations for example, the ability to move laterally with theadditive manufacturing element remaining in its relative orientation tothe roadway course. This may improve effectiveness, efficiency, and rateof operational performance. In some examples, the repair of light crackfeatures may be improved by multiple passes of a seal coating systemover the region under treatment. The ability to move laterally to such arepair location may be one of many such examples that may be improvedwith use of omnidirectional drive capabilities.

Artificial Intelligence and Machine Learning in Mobile AdditiveManufacturing

An Addibot may be configured to utilize various degrees of dataprocessing equipment during the course of its operations, and variousaspects of its operations may be therefore automated. These automationaspects may define one of the types of operations whose automationeffectiveness may be improved by the incorporation of machine learningor more generally artificial intelligence (which may also be classifiedas cognitive computing.) As shall be described in following sectionsthere are also general aspects of Addibot type operations that may beconfigured to utilize artificial intelligence aspects.

In a general way of looking at artificial intelligence, a softwareprogram, which may in some examples be enhanced with customizedcomputing and sensing hardware, is configured to performs task such asimage or pattern recognition, evaluate performance of the task andadjust the operational aspects to improve performance. There may benumerous manners and algorithms that may be used to perform machinelearning or cognitive computing. An example of artificial intelligenceprocessing with particular reference to image processing may be found inthe U.S. Pat. No. 9,904,889 entitled METHODS AND SYSTEMS FOR ARTIFICIALCOGNITION the contents of which were previously included by reference.These algorithms, processes and processing flows may be applied to thevarious uses of machine learning as described herein. It may also benoted that variations on these techniques and processes may naturally beadopted, and in some examples different types of artificial intelligencealgorithms may be applied to the operations as described.

In an example, an Addibot may be optimized to perform repairs of cracksin a roadway surface. Amongst the tasks that are inherently performed inthese operations is the imaging of a roadway and processing the relatedimages to determine the presence of crack type features in the images.Cracks may run in the direction of traffic flow of a roadway, orperpendicular to such traffic, and more generally at any generaldirection in between. An artificial intelligence algorithm may betrained with many types of examples of different cracks. In someexamples, a crack may have some or all of its structure previouslytreated to fill the crack, the algorithm may be trained to discern thedifference from such a filled crack and an unfilled crack and may evendetermine if a filled crack nevertheless requires a subsequent repairoperation. Even when the determination of a crack is made, other aspectsof the imaging that a cognitive intelligence system may work on is todetermine parametric aspects of the crack. For example, how deep, howwide, and how graded the sidewalls of the cracks may be relevantinformation to extract efficiently from the scanning information. Partof the learning may be to determine effective alterations of theparameters of the imaging and sensing equipment such as in nonlimitingexamples, the intensity of irradiation, the wavelength, or bands ofwavelengths to use, as well as the supplementation of imaging data withother techniques such as profilometry or sonography.

In some examples, the artificial intelligence system may be trained torecognize cracks and discern them from other defects such as potholesand adjust processing to the different defect type. The algorithms ofthe artificial intelligence may utilize in non-limiting examples,k-means clustering, adaptive resonance, reinforcement learning,Q-learning, or neural network-based models for this and all artificialintelligence algorithmic learning approaches discussed within thepresent specification. For crack processing, the artificial intelligencesystem may discern that a non-repaired crack is a certain depth andwidth with a certain cross sectional profile and that the most effectivemeans of filling is to apply a certain type of crack filling material ata certain temperature with a certain type of post processing such asrolling as a non-limiting example. The Addibot may have a second imagingsystem trained at observing the underlying roadway after a repairoperation has been prepared. The artificial intelligence system may haveinitially been trained with exemplary images of roadway features thatare cracks and non-cracks as well as for the cracks exemplary images ofeffective and non-effective repair of the cracks. With this training,the artificial intelligence system may learn effective process stepsthat produce an effective result when imaged by the second imagingsystem or another imaging system that can provide feedback to theartificial intelligence system. It may be possible that the artificialintelligence may learn gradations in the effectiveness of the crackrepair or other roadway repair or construction activity and furtherimprove the processing effectiveness. In some cases, the environmentsuch as temperature, degree of sunlight or moonlight and such variablesmay create variation in the imagery obtained by the system, here too theartificial intelligence system may learn to interpret the imagery andadjust processing conditions as appropriate.

In some examples, an artificial intelligence system may learn torecognize different types of defects ranging from overall defectcategories; such as cracks, potholes, missing pavement, missing lineagesuch as painted border lines and the like; to more specificcategorization like different types of crack types. The artificialintelligence system may determine, for example that a particular cracktype may require a customized processing such as a sand blasting, heattreatment or chemical pretreatment for example. In some examples, animage may include evidence of previous repair attempts.

The actual process employed may vary based on the observation of theseprevious repairs. As well, if the repair was performed by the Addibotsystem previously, the artificial intelligence system may include theobservation of the repair as a time progression of a particular repairprotocol. The artificial intelligence system may assess theeffectiveness of the previous repair much as it would use the imagery ofa second imaging system to assess the effectives. In other examples, adifferent type of analysis may be performed on an aged sample based onexpected progression of the repair under weathering conditions.

In some examples, an artificial intelligence system may be used tocalculate paths taken by an Addibot. Different speeds and direction maybe used for efficiency and effectiveness of a repair or constructionaction. As has been discussed herein, Mecanum wheels and othermultidirectional wheel types may allow for increased flexibility. Theincreased flexibility may create a more complex modelling environment.An artificial intelligence system may be particularly effective inrecognizing patterns of movements of the Addibot in reference to aparticular task and its associated path of movement to accomplish thetask. As a non-limiting example, one or more Addibots may be configuredto repair a parking lot surface, blast clean existing painted lines andthen repainting the lines in a different configuration. An artificialintelligence system may recognize the task and determine an effectiverepair protocol taking into the analysis factors such as environmentaltemperature, humidity and the drying rate of the repair materialsemployed and the paints employed which may invoke paths which do notcross over certain cracks that may not be cured at a certain time as anon-limiting example. In some examples, the path may include informationprovided by scanning of the work area with aerial views such as thoseprovided from a drone-based survey.

In some examples, an Addibot may release material from a two-dimensionalmatrix of printing elements. The process may allow repair protocols tooccur at relatively rapid rates. The rapid rate of processing mayincrease the complexity of modelling the repair protocol as effects suchas wind and thermal interactions influenced by the movement may becomeincreasingly important as the speed increases. An artificialintelligence system may invoke machine learning protocols tocharacterize results at higher speeds.

In some examples, an artificial intelligence processing engine may belocated on a server or the cloud and interact with Addibots viacommunication channels such as wireless and wired communication. In someexamples a WiFi signal may be used to communicate with a team ofAddibots each receiving information and in some examples control signalsfrom the artificial intelligence processing engine. In some hybridexamples, artificial intelligence capabilities may reside both on aserver/cloud-based infrastructure as well as locally to the Addibots orin one or more Addibots of a team itself.

Artificial Intelligence may be used, in some examples, to coordinatescheduling as part of the path planning of Addibots for repair orconstruction purposes. The artificial intelligence algorithms may takeinputs of weather, climate, traffic patterns and roadway materialsand/or construction techniques to coordinate the scheduling. In someexamples, the artificial intelligence analysis may anticipate periods ofleast traffic impact, or cost or other such metrics of optimization.Safety of the work team, and Addibot hardware may be included in themetrics of evaluation for the algorithms.

A team of Addibots may utilize materials at differing rates for theindividuals. An artificial intelligence capability may analyze patternsof materials usage and adjust individual Addibot scopes and pathprogramming to optimize active time of work. In some examples units mayresupply the Addibots. The scheduling of resupply may be coordinatedwith pattern recognition of optimized path. In some examples, Addibotsmay return to a central supply to obtain more resources. Theoptimization of wait times at a resupply locations may be a parameter tooptimize goals of the machine learning units.

Omnidirectional Drive Schemes

Referring to FIG. 9A, a close up of a Mecanum type omnidirectional drivecomponent 910 is illustrated. The Mecanum wheel is made up of smalleroblate cylindrical roller components 911 that are oriented at an angleto the axis of the wheel. In a typical configuration, shown in FIG. 9B,four Mecanum wheels 920, 922, 924 and 926 may be oriented at the cornersof the system. Each of the wheels may have an independent motor 921,923, 925 and 927 which can be independently driven in a clockwise orcounterclockwise direction. Various combinations of clockwise orcounterclockwise, which may also be referred to as forward and reverse,driving of the individual motors may be achieved due to this independentdriving. Referring to FIG. 9C, some various general movement directionsthat may be portrayed with different combinations of clockwise andcounterclockwise drive on the wheels. The directions include forward947, left 941, forward left 940, right 945, forward right 946, reverse943, reverse left 942, and reverse right 944. As well rotation aroundthe center point counter clockwise 930 and clockwise 935.

Referring to FIG. 9D, the directional combination is illustrated for anexemplary Mecanum combination of wheels the general movement directionsare marked with black arrows and numbered as described in FIG. 9C. Foreach of these directions, the corresponding direction of travel isindicated schematically for each of the wheels. Clockwise andcounterclockwise directions of the motors are indicated by respectivewhite directional arrows. For the case where the wheels do not rotate anX is indicated at the wheel position. Referring to FIG. 9E, therespective directions are shown are shown for a three wheel—“omni wheel”implementation. And, referring to FIG. 9F, the respective directions areshown for a four wheel—“omni wheel” implementation.

Referring to FIG. 10A, an example path 1002 of an Addibot 1001 equippedwith omnidirectional drive systems. A curved path 1002 may be obtainedwithout steering while controlling the directions of the individualwheels to perform the task. Referring to FIG. 10B, an illustration ofdepositing a deposition 1012 on a surface with an Addibot 1011configured with an omnidirectional drive system is illustrated. In anexample the Addibot 1011 may proceed along a path and then make a turnto move the body around an axis point (with a zero radius turn) toproceed at a 90-degree course to the initial direction. With another 90degrees turn, the Addibot may proceed without running backwards or overa previous deposition. Referring next to FIG. 10C an Addibot 1021 isillustrate in the treatment of a crack 1022. The crack may have ageneral direction that is across the roadway. Using omnidirectionaldrive, the Addibot may proceed towards the right-side direction relativeto FIG. 10C while depositing a coating to treat the crack, a novelmanner to deposit with a mobile additive manufacturing system where thedrive moves along a printing path. Furthermore, referring to FIG. 10D,an Addibot 1031 may progress along a complicated path 1032 which may beachieved with an omnidirectional drive system of the Addibot 1031without the need for a steering system, and therefore, without thelimitation on the radius of such turning. Therefore, numerouscomplicated paths of movements may be engaged with an omnidirectionaldrive system which may allow for free path planning of the depositionprocess of a mobile additive manufacturing system.

Addibots for Brine Treatment

Weather sensing units which may be connected to artificial intelligencealgorithms, in some examples, may drive a need to apply a treatment ofbrine to roadways to maximize roadway performance under cold weatherconditions. An Addibot may provide unique capability of directedapplication of selectable regions based on models of temperature andprecipitation. In some examples, the amount of application, and thetiming and number of times of application of a surface may be systemparameters.

General Aspects

Accordingly, in some examples disclosed in this disclosure, a mobileadditive manufacturing apparatus, which may be called an Addibot, may beconfigured to comprise a drive system which may be operative to move theapparatus along a surface. In some examples the Addibot may functionwith no physical tether. Advanced drive systems may incorporateomnidirectional drive capabilities without or in addition to steeringcomponents. In steered systems the direct drive components may move in ageneral forward and reverse direction. An omnidirectional drivecomponent can directly impart other movements such as translationalmovements, to forward and back, turned movements around the center ofmotion, and turns during a general translational movement. An example ofan omnidirectional drive component may be Mecanum wheels driven byindependently controllable motors.

In addition, the Addibot may comprise a navigation system which amongother functions may determine the Addibots' current location and itscurrent bearing or direction that it would travel in when caused to moveor is travelling in if moving.

The Addibot may additionally comprise a controller capable of executingcode which may perform an algorithmic function. In some examples such acontroller may also be classified as an algorithmic processor. Thecontroller may also provide controlling signals to other elements of theAddibot. The controller may include hardware and encoded programstailored to perform cognitive functions, machine learning or artificialintelligence. In some examples, the controller may interact withcommunication systems to link to external “control nodes” that can withcommunication function as part of the overall controller function.

The Addibot may additionally comprise an additive manufacturing systemto deposit a material or combination of materials in prescribedlocations across the surface that the Addibot is on or will move toduring its processing. The additive manufacturing system may addmaterial to a surface based on a digital model that may be processed inone or more controllers that may be located in the Addibot.

The origin of the digital model may be determined externally to theAddibot or alternatively may be determined by sensing or otherprocessing of the Addibot or may be a combination of external modeldefinition combined with the data related to sensing apparatus withinthe Addibot. Artificial intelligence algorithms may be used in thegeneration and optimization of models.

The systems that the Addibot has may be powered by a power systemcapable of providing power to operate at least the drive system, thenavigation system, the control system, and the additive manufacturingsystem of the Addibot. In some examples multiple power systems may bepresent in an Addibot.

The additive manufacturing system of an Addibot may include manydifferent types and definitions capable of adding material based on adigital model in controlled fashion. In some examples, the additivemanufacturing system may comprise a three-dimensional (“3D”) printinghead. The printing head may include a spray system that may sprayliquids such as pavement sealers upon a surface. In some examples, thespray system may rotate while it sprays material. In other examples, arotating blade which may be flexible may scrape sealing material acrossa surface to distribute it across a surface while the mobile apparatusmoves.

In some examples, the Addibot may also comprise a vision system. Thevision system may be operant to create a digital model of the topographyof a surface in a region proximate to the mobile additive manufacturingapparatus. The vision system may operate on or within the Addibot anduse a variety of detection schemes for analyzing the surface andcreating the model of the surface including light or laser-based imagingtechniques or other electromagnetic radiation-based imaging includinginfrared, ultraviolet or other electromagnetic radiation sources. Insome examples, the vision system may utilize sound-based radiations tocreate a digital model of its surroundings which may include the surfacein the region of the Addibot. In other examples, the Addibot may deploya physical sensor to determine the topography of the surface in a regionstudied by the vision system. A controller located within the Addibotmay initiate the operation of the vision system and may receive signalsin response to the metrology that the vision system performs. In otherexamples, the Addibot may communicate with a vision system that islocated external to itself or on another Addibot for example. Any ofthese vision systems may provide their digitized data to systemsoperating artificial intelligence algorithms which may enhance patternrecognitions effectiveness and also operational speed.

In some examples, the Addibot may also comprise a material storagesystem capable of storing at least a first material to be supplied tothe additive manufacturing system. The stored material may includesolids, powders, gels, liquids, or gasses, to mention some non-limitingexamples. In some examples, the material may be in wire forms or in someexample may exist as physical solid entities which are placed by theadditive manufacturing system. The material storage system may maintaina storage condition for the material by controlling an environmentalcondition. The condition that may be controlled may include one or moreof temperature or pressure of the material.

In some examples, the Addibot may also comprise a surface preparationsystem. The surface preparation system may be capable of removing one ormore of flaked surface material, dust, dirt, and debris from the surfaceregion in a region in advance of the additive manufacturing apparatus.Since the Addibot may move or when stationary the additive manufacturingsystem within the Addibot may move in a direction, the surfacepreparation system may be operant to process a region of the surfacewhere the additive manufacturing system on its own or under the drivesystem of the Addibot may move to.

In some examples, the Addibot may also comprise a communication systemthat may be capable of transmitting signals outside the mobile additivemanufacturing apparatus. In some examples users may use communicationssystems external to the Addibot in transmitting a control signal orcontrol signals to the Addibot. The communication system may also becapable of receiving signals originating outside of the mobile additivemanufacturing apparatus. In some examples, the signals transmitted orreceived may comprise one or more of radiofrequency signals, infraredsignals, optical signals or sound-based signals or emissions asnon-limiting examples. In some examples the communication system mayfunction to sense the environment of the mobile additive manufacturingapparatus. A communication protocol through the communication system mayinvolve the use of artificial intelligence techniques that may beoperating either or both at the unit or remote from the unit. A team ofAddibots may communicate with a local processing node which may performartificial intelligence techniques. Alternative one or all of theprocessing systems of the Addibot, a team of Addibots, a localprocessing node or a remote processing node may act with artificialintelligence techniques. Sensing may occur in addition to signaltransmission function. In some examples, there may be multiplecommunication and/or sensing systems within an Addibot.

There may be numerous methods related to a mobile additive manufacturingapparatus. In some examples a user may transmit a signal to an Addibotwhich may include any of the types of examples of apparatus that havebeen described. The transmitted signal may cause the Addibot to nextdeposit a first layer of material on a surface utilizing systems of theAddibot. The Addibot may, in continued response to the initial signal,move from a first location to a second or different location. Aftermoving the Addibot may in further continued response to the initialsignal deposit a second layer of material. The makeup of the first layerand second layer of material may be different in composition or physicalaspects such as thickness or may be identical except in the aspect thatit is located in a second location.

In some examples, the methods may additionally include omnidirectionaldrive system aspects.

In some examples, the apparatus may include artificial intelligenceprocessing capability. The artificial intelligence system may operate asa discrete or separate system or may be a sub-system of the generalcontroller of the Addibot. In some examples, the artificial intelligencesystem may include an artificial intelligence chip, circuit board orassembly which may be customized to interface with some or all of thesystems of an Addibot.

In some examples, the methods may additional include spray systems todistribute material such as pavement sealant. In some examples themethods may include rotational flexible blade systems to distributematerials such as pavement sealant.

In some examples, the methods may additionally include a step to performa metrology process to measure the topography of a region of a surface.This may typically be in a region proximate to the Addibot or in aregion that the Addibot will move to. In some examples additional stepsin the method may include processing the result of the metrology processand using the result of the processing to control the additivemanufacturing system of the Addibot. The results of the metrology may beprovided to a controller with artificial intelligence capabilities.

In some examples the methods relating to processing by an Addibot mayinclude the step of depositing a layer where a material comprises water.In some of these examples, the surface upon which the material isdeposited may be comprised of water. In some of these examples, thesurface comprised of water may be a surface where the water is in asolid form, which may be water ice.

Implementations may include special forms of drive systems that allowfor omni-directional movement. This may include wheel systems that allowfor linear movement at any or many possible angles with respect to thecenter of mass of the apparatus. This may also include drive systemsthat turn with no turning radius, allowing for full orientation of theapparatus at any angle of rotation with respect to the center of mass ofthe apparatus. If these two characteristics are combined in a drivesystem, the exemplary drive system may be able to move in a particularlinear path over a surface while, at the same time, changing itsrotational orientation. Combining this exemplary drive system with adistribution system that is fixed to the drive system but operantoutside of the area between or under the components of the drive system,this distribution system may be guided in a particular path over asurface that allows this distribution system to cover the entire surfaceit is passing over without the area between or under the components ofthe drive system ever passing over any area that was already distributedupon. This creates a completely novel manner of controlling mobility ina mobile additive manufacturing robot.

One general aspect includes a mobile additive manufacturing apparatusincluding: an omnidirectional drive system operative to move theapparatus along a surface, where the omnidirectional drive systememploys at least a first omnidirectional wheel directly attached to afirst motor, and where the first motor has operational modes to beengaged in a forward moving, reverse moving or stationary configuration,a navigation system to determine location; a mobile additivemanufacturing apparatus controller capable of executing algorithms andproviding control signals, a vision system capable of scanning thesurface and measuring a topography of the surface; an artificialintelligence processing system, where the artificial intelligenceprocessing system includes a program which executes at least a firstalgorithm, where the first algorithm utilizes one or more of k-meansclustering, adaptive resonance, reinforcement learning, or q-learningprocessing, and where a data-bus of the vision system directly couplesto the artificial intelligence processing system, and where theartificial intelligence processing system uses one or more of a traineddatabase of roadway defects and a dynamically trained database ofadditive manufacturing processed roadway defects processed by the mobileadditive manufacturing apparatus; an additive manufacturing system todeposit at least a first material in a prescribed location on thesurface according to a digital model processed by one or more of themobile additive manufacturing apparatus controller or the artificialintelligence processing system, where the additive manufacturing systemdeposits material while the omnidirectional drive system changes adirection of movement of the mobile additive manufacturing apparatususing a change in an operational mode of at least the firstomnidirectional wheel; and a power system capable of providing power tooperate at least the drive system, navigation system, mobile additivemanufacturing apparatus controller and additive manufacturing system.Other embodiments of this aspect include corresponding computer systems,apparatus, and computer programs recorded on one or more computerstorage devices, each configured to perform the actions of the methods.

Implementations may include one or more of the following features. Themethod where the additive manufacturing system deposits seal coatingmaterial where the one or more of a spray system or drip systemcomponents are attached to a rotational gantry, where a rotationalorientation is set according to the first digital model. The methodwhere the first digital model includes a path plan where theomnidirectional drive system is used to create a continuous movementflow of the mobile additive manufacturing apparatus during operation ofthe additive manufacturing system where wheels of the omnidirectionaldrive system do not pass over portions of the surface that have beenprocessed with the additive manufacturing system. Implementations of thedescribed techniques may include hardware, a method or process, orcomputer software on a computer-accessible medium.

CONCLUSION

A number of examples of the present disclosure have been described.While this specification contains many specific implementation details,they should not be construed as limitations on the scope of anyinventions or of what may be Claimed, but rather as descriptions offeatures specific to particular examples of the present disclosure.Specifically seal coating examples have been described, where numerousother functions may be possible within the scope of the disclosureparticularly where an omnidirectional drive system may allow for themobile additive manufacturing system to move the additive manufacturingelements over a location which will not have wheels passing overthereafter and be flexible to cover a wide range of paths and workingsurface shapes.

Certain features that are described in this specification in the contextof separate examples can also be implemented in combination in a singleembodiment. Conversely, various features that are described in thecontext of a single embodiment can also be implemented in combination inmultiple examples separately or in any suitable sub-combination.Moreover, although features may be described above as acting in certaincombinations and even initially Claimed as such, one or more featuresfrom a Claimed combination can in some cases be excised from thecombination, and the Claimed combination may be directed to asub-combination or variation of a sub-combination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multitasking and parallel processingmay be advantageous.

Moreover, the separation of various system components in the examplesdescribed above should not be understood as requiring such separation inall examples, and it should be understood that the described componentsand systems can generally be integrated together in a single product orpackaged into multiple products.

Thus, particular examples of the subject matter have been described.Other examples are within the scope of the following Claims. In somecases, the actions recited in the Claims can be performed in a differentorder and still achieve desirable results. In addition, the processesdepicted in the accompanying figures do not necessarily require theparticular order shown, or sequential order, to achieve desirableresults. In certain implementations, multitasking and parallelprocessing may be advantageous. Nevertheless, it will be understood thatvarious modifications may be made without departing from the spirit andscope of the Claimed invention. While the disclosure has been describedin conjunction with specific examples, it is evident that manyalternatives, modifications, and variations will be apparent to thoseskilled in the art in light of the foregoing description. Accordingly,this description is intended to embrace all such alternatives,modifications and variations as fall within its spirit and scope.Certain features that are described in this specification in the contextof separate embodiments can also be implemented in combination in asingle embodiment. Conversely, various features that are described inthe context of a single embodiment can also be implemented incombination in multiple embodiments separately or in any suitablesub-combination. Moreover, although features may be described above asacting in certain combinations and even initially Claimed as such, oneor more features from a Claimed combination can in some cases be excisedfrom the combination, and the Claimed combination may be directed to asub-combination or variation of a sub-combination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multitasking and parallel processingmay be advantageous.

Moreover, the separation of various system components in the embodimentsdescribed above should not be understood as requiring such separation inall embodiments. Examples of Addibots may include all system componentsor a subset of components and may act in multiples to perform variousfunctions. Thus, while particular embodiments of the subject matter havebeen described, other embodiments are within the scope of the followingClaims.

What is claimed is:
 1. A method for applying a first material to asurface, the method comprising: loading at least the first material intoat least a first mobile additive manufacturing apparatus and a secondmobile additive manufacturing apparatus, wherein each of the firstmobile manufacturing apparatus and the second mobile manufacturingapparatus comprise: a navigation system to determine location, a mobileadditive manufacturing apparatus controller capable of executingalgorithms and providing control signals, a vision system capable ofscanning the surface and measuring a topography of the surface, anadditive manufacturing system to deposit at least the first material ina prescribed location on the surface according to a digital modelprocessed by the mobile additive manufacturing apparatus controller, apower system capable of providing power to operate at least the drivesystem, navigation system, mobile additive manufacturing apparatuscontroller and additive manufacturing system, and a communicationsystem; loading software algorithms into an artificial processing systemwith a global communication system, wherein the global communicationsystem provides communication between at least the first mobile additivemanufacturing apparatus, the second mobile additive manufacturingapparatus and the artificial intelligence processing system;communicating an objective for applying the first material to thesurface to the artificial intelligence processing system, wherein theartificial intelligence processing system comprises a program whichexecutes at least a first algorithm; receiving information at theartificial intelligence processing system from the first mobile additivemanufacturing apparatus comprising at least a location determined by thenavigation system of the first mobile additive manufacturing apparatus;processing the received information with the artificial intelligenceprocessing system with at least a first artificial intelligencealgorithm; and communicating at least movement plans from the artificialintelligence processing system to at least each of the first mobileadditive manufacturing apparatus and the second mobile additivemanufacturing apparatus of the team.
 2. The method of claim 1 whereinthe artificial intelligence processing system comprises an artificialintelligence processing chip.
 3. The method of claim 2 furthercomprising: receiving information at the artificial intelligenceprocessing system from the first mobile additive manufacturing apparatuscomprising at least an image determined by the vision system of thefirst mobile additive manufacturing apparatus; processing the receivedinformation with the artificial intelligence processing system with atleast a second artificial intelligence algorithm; and communicating atleast deposition plans of at least the first material to at least eachof the first mobile additive manufacturing apparatus and the secondmobile additive manufacturing apparatus of the team.
 4. The method ofclaim 3 wherein at least the first mobile additive manufacturingapparatus comprises an artificial intelligence processing chip.
 5. Themethod of claim 3 further comprising communicating at least a seconddeposition plan of at least a second material comprising a paintformulation.
 6. The method of claim 1 further comprising communicatingat least movement plans of the first mobile additive manufacturingsystem and the second mobile additive manufacturing system to a roadwayinformation processing system, wherein the roadway informationprocessing system communicates information to vehicles using a roadwayof the roadway information processing system, and wherein thecommunication of information related to the movement plan to thevehicles can facilitate their safe movement through the portion of theroadway occupied by at least the first mobile additive manufacturingsystem.
 7. A mobile additive manufacturing apparatus for depositing afirst seal coating material comprising: a navigation system to determinelocation; a controller capable of executing algorithms and providingcontrol signals, a vision system capable of scanning a first surface andmeasuring a topography of the first surface as the mobile additivemanufacturing apparatus moves over the first surface; a drive system tomove the additive manufacturing apparatus; an additive manufacturingsystem to deposit at least the first material for seal coating in aprescribed location on the first surface according to a digital modelprocessed by the controller; a power system capable of providing powerto operate at least the drive system, navigation system, controller andadditive manufacturing system; a chassis, wherein the chassis supportsall of the navigation system, the controller, the vision system, thedrive system, the additive manufacturing system and the power system;and a rotary dispensing system, wherein the rotary dispensing systemcomprises a rotary gantry, wherein the rotary gantry is moved by a motordriving the gantry around a central axis supported by the chassis. 8.The apparatus of claim 7 wherein the rotary gantry supports at least afirst spray dispensing nozzle, and wherein the first seal coatingmaterial is passed through the rotary dispensing system to the nozzle.9. The apparatus of claim 8 wherein the drive system comprises at leasta first omnidirectional wheel directly attached to a first motor,wherein the drive system can move the mobile additive manufacturingapparatus in more directions than forward and backward by adjusting theoperating conditions of the first motor.
 10. The apparatus of claim 9wherein the rotary gantry moves a rotation angle of the rotary gantryrelative to the chassis in response to the adjusted conditions of thefirst motor.
 11. The apparatus of claim 10 wherein the rotary gantrysupports at least a first sensor, wherein the sensor senses the rate ofdispensing of the first seal coating material.
 12. The apparatus ofclaim 7 wherein the rotary gantry comprises at least a first squeegeeand at least a first nozzle, wherein the rotary gantry continuouslyrotates around the central axis while the nozzle dispenses the firstseal coating material, and wherein the rotating squeegee spreads out thefirst seal coating material on the first surface as the mobile additivemanufacturing apparatus moves across the first surface.
 13. Theapparatus of claim 12 wherein the rotary gantry further comprises asecond squeegee, wherein the first squeegee and the second squeegee aredeployed on distal ends of the rotary gantry, and wherein at least thefirst nozzle dispenses the first seal coating material into a spacebetween the first squeegee and the second squeegee.
 14. The apparatus ofclaim 12 wherein the rotary gantry further comprises at least a firstsensor, wherein the first sensor measures an amount of materialdispensed by the nozzle.
 15. The apparatus of claim 12 wherein therotary gantry further comprises at least a second sensor, wherein thesecond sensor measures an amount of material dispensed by the nozzle.16. A method of seal coating a first surface, the method comprising:loading at least a first seal coating material into at least a firstmobile additive manufacturing apparatus, wherein the first mobilemanufacturing apparatus comprises: a navigation system to determinelocation, a controller capable of executing algorithms and providingcontrol signals, a vision system capable of scanning a first surface andmeasuring a topography of the first surface as the mobile additivemanufacturing apparatus moves over the first surface, a drive system tomove the additive manufacturing apparatus, an additive manufacturingsystem to deposit at least the first material for seal coating in aprescribed location on the first surface according to a digital modelprocessed by the controller, a power system capable of providing powerto operate at least the drive system, navigation system, controller andadditive manufacturing system, a chassis, wherein the chassis supportsall of the navigation system, the controller, the vision system, thedrive system, the additive manufacturing system and the power system,and a rotary dispensing system, wherein the rotary dispensing systemcomprises a rotary gantry, wherein the rotary gantry is moved by a motordriving an element around a central axis supported by the chassis;moving the first mobile additive manufacturing apparatus with the drivesystem, wherein an amount of movement is controlled by the digitalmodel; and dispensing the seal coating material on the first surfacewhile the first mobile additive manufacturing apparatus is moving,wherein an amount of the seal coating material dispensed is controlledby the digital model.
 17. The method of claim 16 wherein the controllercomprises an artificial intelligence processing chip, and an artificialintelligence algorithm is used to create the digital model.
 18. Themethod of claim 16 wherein the rotary gantry supports at least a firstspray dispensing nozzle, and wherein the first seal coating material ispassed through the rotary dispensing system to the nozzle.
 19. Themethod of claim 18 wherein the first surface is one of a driveway, aroadway, a parking lot or a roof.
 20. The method of claim 16 wherein therotary gantry comprises at least a first squeegee and at least a firstnozzle, wherein the rotary gantry continuously rotates around thecentral axis while the nozzle dispenses the first seal coating material,and wherein the rotating squeegee spreads out the first seal coatingmaterial on the first surface as the mobile additive manufacturingapparatus moves across the first surface.